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At least 865 records · Page 48

Magnetospheric MultiScale (MMS) System Manager

The Magnetospheric MultiScale (MMS) mission is an ambitious NASA space science mission in which 4 spacecraft are flown in tight formation about a highly elliptical orbit. Each spacecraft has multiple instruments that measure particle and field compositions in the Earths magnetosphere. By controlling the members relative motion, MMS can distinguish temporal and spatial fluctuations in a way that a single spacecraft cannot.To achieve this control, 2 sets of four maneuvers, distributed evenly across the spacecraft must be performed approximately every 14 days. Performing a single maneuver on an individual spacecraft is usually labor intensive and the complexity becomes clearly increases with four. As a result, the MMS flight dynamics team turned to the System Manager to put the routine or error-prone under machine control freeing the analysts for activities that require human judgment.The System Manager is an expert system that is capable of handling operations activities associated with performing MMS maneuvers. As an expert system, it can work off a known schedule, launching jobs based on a one-time occurrence or on a set reoccurring schedule. It is also able to detect situational changes and use event-driven programming to change schedules, adapt activities, or call for help.

Ground System Expert Automation↗

Complexity and Pilot Workload Metrics for the Evaluation of Adaptive Flight Controls on a Full Scale Piloted Aircraft

Flight research has shown the effectiveness of adaptive flight controls for improving aircraft safety and performance in the presence of uncertainties. The National Aeronautics and Space Administration's (NASA)'s Integrated Resilient Aircraft Control (IRAC) project designed and conducted a series of flight experiments to study the impact of variations in adaptive controller design complexity on performance and handling qualities. A novel complexity metric was devised to compare the degrees of simplicity achieved in three variations of a model reference adaptive controller (MRAC) for NASA's F-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Full-Scale Advanced Systems Testbed (Gen-2A) aircraft. The complexity measures of these controllers are also compared to that of an earlier MRAC design for NASA's Intelligent Flight Control System (IFCS) project and flown on a highly modified F-15 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois). Pilot comments during the IRAC research flights pointed to the importance of workload on handling qualities ratings for failure and damage scenarios. Modifications to existing pilot aggressiveness and duty cycle metrics are presented and applied to the IRAC controllers. Finally, while adaptive controllers may alleviate the effects of failures or damage on an aircraft's handling qualities, they also have the potential to introduce annoying changes to the flight dynamics or to the operation of aircraft systems. A nuisance rating scale is presented for the categorization of nuisance side-effects of adaptive controllers.

pilot workload metrics↗

Safe Maneuvering Envelope Estimation Based on a Physical Approach

This paper discusses a computationally efficient algorithm for estimating the safe maneuvering envelope of damaged aircraft. The algorithm performs a robust reachability analysis through an optimal control formulation while making use of time scale separation and taking into account uncertainties in the aerodynamic derivatives. This approach differs from others since it is physically inspired. This more transparent approach allows interpreting data in each step, and it is assumed that these physical models based upon flight dynamics theory will therefore facilitate certification for future real life applications.

aerodynamics↗

Lunar Reconnaissance Orbiter Orbit Determination Accuracy Analysis

Results from operational OD produced by the NASA Goddard Flight Dynamics Facility for the LRO nominal and extended mission are presented. During the LRO nominal mission, when LRO flew in a low circular orbit, orbit determination requirements were met nearly 100% of the time. When the extended mission began, LRO returned to a more elliptical frozen orbit where gravity and other modeling errors caused numerous violations of mission accuracy requirements. Prediction accuracy is particularly challenged during periods when LRO is in full-Sun. A series of improvements to LRO orbit determination are presented, including implementation of new lunar gravity models, improved spacecraft solar radiation pressure modeling using a dynamic multi-plate area model, a shorter orbit determination arc length, and a constrained plane method for estimation. The analysis presented in this paper shows that updated lunar gravity models improved accuracy in the frozen orbit, and a multiplate dynamic area model improves prediction accuracy during full-Sun orbit periods. Implementation of a 36-hour tracking data arc and plane constraints during edge-on orbit geometry also provide benefits. A comparison of the operational solutions to precision orbit determination solutions shows agreement on a 100- to 250-meter level in definitive accuracy.

Gravitation↗

Orbit Determination Accuracy Analysis of the Magnetospheric Multiscale Mission During Perigee Raise

The Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF) will provide orbit determination and prediction support for the Magnetospheric Multiscale (MMS) mission during the missions commissioning period. The spacecraft will launch into a highly elliptical Earth orbit in 2015. Starting approximately four days after launch, a series of five large perigee-raising maneuvers will be executed near apogee on a nearly every-other-orbit cadence. This perigee-raise operations concept requires a high-accuracy estimate of the orbital state within one orbit following the maneuver for performance evaluation and a high-accuracy orbit prediction to correctly plan and execute the next maneuver in the sequence. During early mission design, a linear covariance analysis method was used to study orbit determination and prediction accuracy for this perigee-raising campaign. This paper provides a higher fidelity Monte Carlo analysis using the operational COTS extended Kalman filter implementation that was performed to validate the linear covariance analysis estimates and to better characterize orbit determination performance for actively maneuvering spacecraft in a highly elliptical orbit. The study finds that the COTS extended Kalman filter tool converges on accurate definitive orbit solutions quickly, but prediction accuracy through orbits with very low altitude perigees is degraded by the unpredictability of atmospheric density variation.

Determination↗

Orbit Determination Accuracy Analysis of the Magnetospheric Multiscale Mission During Perigee Raise

The Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF) will provide orbit determination and prediction support for the Magnetospheric Multiscale (MMS) mission during the mission's commissioning period. The spacecraft will launch into a highly elliptical Earth orbit in 2015. Starting approximately four days after launch, a series of five large perigee-raising maneuvers will be executed near apogee on a nearly every-other-orbit cadence. This perigee-raise operations concept requires a high-accuracy estimate of the orbital state within one orbit following the maneuver for performance evaluation and a high-accuracy orbit prediction to correctly plan and execute the next maneuver in the sequence. During early mission design, a linear covariance analysis method was used to study orbit determination and prediction accuracy for this perigee-raising campaign. This paper provides a higher fidelity Monte Carlo analysis using the operational COTS extended Kalman filter implementation that was performed to validate the linear covariance analysis estimates and to better characterize orbit determination performance for actively maneuvering spacecraft in a highly elliptical orbit. The study finds that the COTS extended Kalman filter tool converges on accurate definitive orbit solutions quickly, but prediction accuracy through orbits with very low altitude perigees is degraded by the unpredictability of atmospheric density variation.

Multiscale↗

Pilot-in-the-Loop Evaluation of a Yaw Rate to Throttle Feedback Control with Enhanced Engine Response

This paper describes the implementation and evaluation of a yaw rate to throttle feedback system designed to replace a damaged rudder. It can act as a Dutch roll damper and as a means to facilitate pilot input for crosswind landings. Enhanced propulsion control modes were implemented to increase responsiveness and thrust level of the engine, which impact flight dynamics and performance. Piloted evaluations were performed to determine the capability of the engines to substitute for the rudder function under emergency conditions. The results showed that this type of implementation is beneficial, but the engines' capability to replace the rudder is limited.

Litt, Jonathan S.↗

Aerodynamic Stability and Performance of Next-Generation Parachutes for Mars Descent

The Low Density Supersonic Decelerator Project is developing a next-generation supersonic parachute for use on future Mars missions. In order to determine the new parachute configuration, a wind tunnel test was conducted at the National Full-scale Aerodynamics Complex 80- by 120-foot Wind Tunnel at the NASA Ames Research Center. The goal of the wind tunnel test was to quantitatively determine the aerodynamic stability and performance of various canopy configurations in order to help select the design to be flown on the Supersonic Flight Dynamics tests. Parachute configurations included the diskgap- band, ringsail, and ringsail-variant designs referred to as a disksail and starsail. During the wind tunnel test, digital cameras captured synchronized image streams of the parachute from three directions. Stereo hotogrammetric processing was performed on the image data to track the position of the vent of the canopy throughout each run. The position data were processed to determine the geometric angular history of the parachute, which were then used to calculate the total angle of attack and its derivatives at each instant in time. Static and dynamic moment coefficients were extracted from these data using a parameter estimation method involving the one-dimensional equation of motion for a rotation of parachute. The coefficients were calculated over all of the available canopy states to reconstruct moment coefficient curves as a function of total angle of attack. From the stability curves, useful metrics such as the trim total angle of attack and pitch stiffness at the trim angle could be determined. These stability metrics were assessed in the context of the parachute's drag load and geometric porosity. While there was generally an inverse relationship between the drag load and the stability of the canopy, the data showed that it was possible to obtain similar stability properties as the disk-gap-band with slightly higher drag loads by appropriately tailoring the geometric porosity distribution.

Low Density Supersonic Decelerator (LDSD)↗

Rigging Test Bed Development for Validation of Multi-Stage Decelerator Extractions

The Low Density Supersonic Decelerator project is developing new decelerator systems for Mars entry which would include testing with a Supersonic Flight Dynamics Test Vehicle. One of the decelerator systems being developed is a large supersonic ringsail parachute. Due to the configuration of the vehicle it is not possible to deploy the parachute with a mortar which would be the preferred method for a spacecraft in a supersonic flow. Alternatively, a multi-stage extraction process using a ballute as a pilot is being developed for the test vehicle. The Rigging Test Bed is a test venue being constructed to perform verification and validation of this extraction process. The test bed consists of a long pneumatic piston device capable of providing a constant force simulating the ballute drag force during the extraction events. The extraction tests will take place both inside a high-bay for frequent tests of individual extraction stages and outdoors using a mobile hydraulic crane for complete deployment tests from initial pack pull out to canopy extraction. These tests will measure line tensions and use photogrammetry to track motion of the elements involved. The resulting data will be used to verify packing and rigging as well, as validate models and identify potential failure modes in order to finalize the design of the extraction system.

Low Density Supersonic Decelerator (LDSD)↗

Navigation Operations for the Magnetospheric Multiscale Mission

The Magnetospheric Multiscale (MMS) mission employs four identical spinning spacecraft flying in highly elliptical Earth orbits. These spacecraft will fly in a series of tetrahedral formations with separations of less than 10 km. MMS navigation operations use onboard navigation to satisfy the mission definitive orbit and time determination requirements and in addition to minimize operations cost and complexity. The onboard navigation subsystem consists of the Navigator GPS receiver with Goddard Enhanced Onboard Navigation System (GEONS) software, and an Ultra-Stable Oscillator. The four MMS spacecraft are operated from a single Mission Operations Center, which includes a Flight Dynamics Operations Area (FDOA) that supports MMS navigation operations, as well as maneuver planning, conjunction assessment and attitude ground operations. The System Manager component of the FDOA automates routine operations processes. The GEONS Ground Support System component of the FDOA provides the tools needed to support MMS navigation operations. This paper provides an overview of the MMS mission and associated navigation requirements and constraints and discusses MMS navigation operations and the associated MMS ground system components built to support navigation-related operations.

Navigation↗

MISL SDK Public Release

The Modular Integrated Stackable Layers (MISL) is a compact space-related computer system that is modular, scalable and reconfigurable. The original goal was to design a space environment capable instrumentation system with a flexible design so that as subsets of requirements changed, it minimized the need for new designs and maximized the reusability of the hardware and software modules. The result is a flexible, economical and small computer system that can be adapted to uses in space environment instrumentation and control. Current applications include habitat system instruments and control, dynamic flight instrumentation in rugged environments, in vehicle communication protocol converters and remote control unit for thruster jets. Future applications are limited only by the imagination!

Delaune, Paul↗

Operational Challenges In TDRS Post-Maneuver Orbit Determination

The GSFC Flight Dynamics Facility (FDF) is responsible for daily and post maneuver orbit determination for the Tracking and Data Relay Satellite System (TDRSS). The most stringent requirement for this orbit determination is 75 meters total position accuracy (3-sigma) predicted over one day for Terra's onboard navigation system. To maintain an accurate solution onboard Terra, a solution is generated and provided by the FDF Four hours after a TDRS maneuver. A number of factors present challenges to this support, such as maneuver prediction uncertainty and potentially unreliable tracking from User satellities. Reliable support is provided by comparing an extended Kalman Filter (estimated using ODTK) against a Batch Least Squares system (estimated using GTDS).

FDF↗

Low Cost Entry, Descent, and Landing (EDL) Instrumentation for Planetary Missions

Missions that involve traversing through a planetary atmosphere are unique opportunities that require elements of entry, descent, and landing (EDL). Many aspects of the EDL sequence are qualified using analysis and simulation due to the inability to conduct appropriate ground tests, however validating flight data are often lacking, especially for missions not involving Earth re-entry. NASA has made strategic decisions to collect EDL flight data in order to improve future mission designs. For example, MEDLI1 and EFT-1 gathered hypersonic pressure and in-depth temperature data in the thermal protection system (TPS). However, the ability to collect EDL flight data from the smaller competed missions, such as Discovery and New Frontiers, has been limited in part due to the Principal Investigator-managed cost-caps (PIMCC). The recent NASA decision to consider EDL instrumentation earlier in the mission design cycle led to the inclusion of a requirement in the Discovery 2014 Announcement of Opportunity which requires all missions that involve EDL to include an Engineering Science Investigation (ESI).2 The ESI would involve sensors for aerothermal environment and TPS; atmosphere, aerodynamics, and flight dynamics; atmospheric decelerator; and/or vehicle structure.3 The ESI activity would be funded outside of the PIMCC.

and Landing↗

UAV Research at NASA Langley: Towards Safe, Reliable, and Autonomous Operations

Unmanned Aerial Vehicles (UAV) are fundamental components in several aspects of research at NASA Langley, such as flight dynamics, mission-driven airframe design, airspace integration demonstrations, atmospheric science projects, and more. In particular, NASA Langley Research Center (Langley) is using UAVs to develop and demonstrate innovative capabilities that meet the autonomy and robotics challenges that are anticipated in science, space exploration, and aeronautics. These capabilities will enable new NASA missions such as asteroid rendezvous and retrieval (ARRM), Mars exploration, in-situ resource utilization (ISRU), pollution measurements in historically inaccessible areas, and the integration of UAVs into our everyday lives all missions of increasing complexity, distance, pace, and/or accessibility. Building on decades of NASA experience and success in the design, fabrication, and integration of robust and reliable automated systems for space and aeronautics, Langley Autonomy Incubator seeks to bridge the gap between automation and autonomy by enabling safe autonomous operations via onboard sensing and perception systems in both data-rich and data-deprived environments. The Autonomy Incubator is focused on the challenge of mobility and manipulation in dynamic and unstructured environments by integrating technologies such as computer vision, visual odometry, real-time mapping, path planning, object detection and avoidance, object classification, adaptive control, sensor fusion, machine learning, and natural human-machine teaming. These technologies are implemented in an architectural framework developed in-house for easy integration and interoperability of cutting-edge hardware and software.

Davila, Carlos G.↗

The Magnetospheric Multiscale Constellation

The Magnetospheric Multiscale (MMS) mission is the fourth mission of the Solar Terrestrial Probe (STP) program of the National Aeronautics and Space Administration (NASA). The MMS mission was launched on March 12, 2015. The MMS mission consists of four identically instrumented spin-stabilized observatories which are flown in formation to perform the first definitive study of magnetic reconnection in space. The MMS mission was presented with numerous technical challenges, including the simultaneous construction and launch of four identical large spacecraft with 100 instruments total, stringent electromagnetic cleanliness requirements, closed-loop precision maneuvering and pointing of spinning flexible spacecraft, on-board GPS based orbit determination far above the GPS constellation, and a flight dynamics design that enables formation flying with separation distances as small as 10 km. This paper describes the overall mission design and presents an overview of the design, testing, and early on-orbit operation of the spacecraft systems and instrument suite.

Space mission design↗

Filter Tuning Using the Chi-Squared Statistic

The Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF) performs orbit determination (OD) for the Aqua and Aura satellites. Both satellites are located in low Earth orbit (LEO), and are part of what is considered the A-Train satellite constellation. Both spacecraft are currently in the science phase of their respective missions. The FDF has recently been tasked with delivering definitive covariance for each satellite.The main source of orbit determination used for these missions is the Orbit Determination Toolkit developed by Analytical Graphics Inc. (AGI). This software uses an Extended Kalman Filter (EKF) to estimate the states of both spacecraft. The filter incorporates force modelling, ground station and space network measurements to determine spacecraft states. It also generates a covariance at each measurement. This covariance can be useful for evaluating the overall performance of the tracking data measurements and the filter itself. An accurate covariance is also useful for covariance propagation which is utilized in collision avoidance operations. It is also valuable when attempting to determine if the current orbital solution will meet mission requirements in the future.This paper examines the use of the Chi-square statistic as a means of evaluating filter performance. The Chi-square statistic is calculated to determine the realism of a covariance based on the prediction accuracy and the covariance values at a given point in time. Once calculated, it is the distribution of this statistic that provides insight on the accuracy of the covariance.For the EKF to correctly calculate the covariance, error models associated with tracking data measurements must be accurately tuned. Over estimating or under estimating these error values can have detrimental effects on the overall filter performance. The filter incorporates ground station measurements, which can be tuned based on the accuracy of the individual ground stations. It also includes measurements from the NASA space network (SN), which can be affected by the assumed accuracy of the TDRS satellite state at the time of the measurement.The force modelling in the EKF is also an important factor that affects the propagation accuracy and covariance sizing. The dominant force in the LEO orbit regime is the drag force caused by atmospheric drag. Accurate accounting of the drag force is especially important for the accuracy of the propagated state. The implementation of a box and wing model to improve drag estimation accuracy, and its overall effect on the covariance state is explored.The process of tuning the EKF for Aqua and Aura support is described, including examination of the measurement errors of available observation types (Doppler and range), and methods of dealing with potentially volatile atmospheric drag modeling. Predictive accuracy and the distribution of the Chi-square statistic, calculated based of the ODTK EKF solutions, are assessed versus accepted norms for the orbit regime.

Covariance Analysis↗

Conjunction Assessment Techniques and Operational Results from the Magnetospheric Multiscale Mission

This paper will describe the results that have been obtained to date during the MMS mission concerning conjunction assessment. MMS navigation makes use of a weak-signal GPS-based system: this allows signals to be received even when MMS is flying above the GPS orbits, producing a highly accurate determination of the four MMS orbits. This data is downlinked to the MMS Mission Operations Center (MOC) and used by the Flight Dynamics Operations Area (FDOA) for both maneuver design and conjunction assessment. The MMS fly in tetrahedron formations around apogee, in order to collect simultaneous particles and fields science data. The original plan was to fly tetrahedra between 10 and 160 km in size; however, after Phase 1a of the mission, the science team requested that smaller sizes be flown if feasible. After analysis (to be detailed in a companion paper), a new minimum size of 7 km was decided upon. Flying at this reduced scale size makes conjunction assessment between the MMS spacecraft even more important: the methods that are used by the MMS FDOA to address this problem will be described in the paper, and a summary given of the previous analyses that went into the development of these techniques. Details will also be given of operational experiences to date. Finally, two CA mitigation maneuver types that have been designed (but never yet required to actually be performed) will also be outlined.

conjunction Assessment↗

Pyrotechnically Actuated Gas Generator Utilizing Aqueous Methanol

A gas-generating device was developed to supplement the ram-air inflation of a supersonic ballute. The device is designed to initially pressurize the ballute following deployment, exposing and orienting its ram-air inlets to free-stream air for complete inflation. The supplemental pressurization decreases the total inflation time, and increases the likelihood of a successful inflation. The device contains a reservoir filled with an aqueous mixture of methanol that, when released in to the interior of the ballute, rapidly vaporizes due to the low ambient pressure. Upon activation of the device, a pair of redundant ring mechanisms initiate pyrotechnic charges that pressurize and rupture the reservoir, resulting in ejection of the methanol in to the ballute. In addition to its role in inflation, the device serves as the structural connection to the ballute. Analytical models were developed for the inflation capability of the device, which were verified using vacuum chamber testing of developmental hardware. Static, deployment, and environmental testing demonstrated the functionality of the ring mechanism and reservoir under several temperature and pressure conditions. Finally, the device was successfully operated during the first Supersonic Flight Dynamics Test (SFDT) of NASA's Low Density Supersonic Decelerator (LDSD) project. The design architecture is scalable to accommodate different quantities of gas generation, can be adjusted to operate in a variety of temperature and atmospheric pressure regimes, and provides a robust device that may be installed with minimal risk to personnel or hardware.

IA↗