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This paper will survey three software systems in development at NASA's Jet Propulsion Laboratory that are the product of many years of research and development in artificial intelligence and related disciplines.
The Jupiter Icy Moons Orbiter (JIMO) mission is currently under study by the Office of Space Science under the Project Prometheus Program. JIMO is examining the use of Nuclear Electric Propulsion (NEP) to carry scientific payloads to three Jovian moons. A potential power system concept includes dual 100 kWe Brayton converters, a deployable pumped loop heat rejection subsystem, and a 400 Vac Power Management and Distribution (PMAD) bus. Many trades were performed in aniving at this candidate power system concept. System-level studies examined design and off-design operating modes, determined startup requirements, evaluated subsystem redundancy options, and quantified the mass and radiator area of reactor power systems from 20 to 200 kWe. In the Brayton converter subsystem, studies were performed to investigate converter packaging options, and assess the induced torque effects on spacecraft dynamics due to rotating machinery. In the heat rejection subsystem, design trades were conducted on heat transport approaches, material and fluid options, and deployed radiator geometries. In the PMAD subsystem, the overall electrical architecture was defined and trade studies examined distribution approaches, voltage levels, and cabling options.
Three NASA centers are working together to address the challenge of operating robotic assets in support of human exploration of the Moon. This paper describes the combined work to date of the Ames Research Center (ARC), Jet Propulsion Laboratory (JPL) and Johnson Space Center (JSC) on a common support framework to control and monitor lunar robotic assets. We discuss how we have addressed specific challenges including time-delayed operations, and geographically distributed collaborative monitoring and control, to build an effective architecture for integrating a heterogeneous collection of robotic assets into a common work. We describe the design of the Robot Application Programming Interface Delegate (RAPID) architecture that effectively addresses the problem of interfacing a family of robots including the JSC Chariot, ARC K-10 and JPL ATHLETE rovers. We report on lessons learned from the June 2008 field test in which RAPID was used to monitor and control all of these assets. We conclude by discussing some future directions to extend the RAPID architecture to add further support for NASA's lunar exploration program.
The utilization of advanced fan designs (including higher bypass ratios) and shorter engine nacelles has highlighted a need for increased fan noise reduction over a broad frequency range. With these observations in mind, an acoustic liner optimization process has been developed to achieve improved broadband liner designs. A series of advanced liner design studies at increasing technology readiness levels has been conducted as the overall optimization methodology has been enhanced. In this work, further validation was pursued through the fabrication and testing of two liner designs for the NASA Glenn DGEN Aero-propulsion Research Turbofan. Specifically, single and three layer liners were designed, fabricated, and tested. Analysis of the predicted attenuation results showed them to generally match expected trends for the conditions considered. The effects of source distribution on predicted directivity were also illustrated through the flexibility of a statistical source model. As part of the analysis, the overall design and evaluation capability was extended such that external observer locations may be included in the optimization process. This enhancement will provide a much wider design space for the development of advanced broadband liners. These preliminary results provide further confidence in the design tools and enhancements made to the overall liner design process.
The performance of an axisymmetric multi-fluid Hall thruster code that incorporates a self-consistent, data-driven closure model for the anomalous electron transport is investigated. Five different operating conditions of the H9 magnetically shielded Hall thruster are simulated with the Jet Propulsion Laboratory’s Hall2De. In order to capture the inherent uncertainty associated with the closure model, O(100) simulations are run for each condition, each of using a coefficient set sampled randomly from a probability distribution. The results of these simulations provide probabilistic predictions of thruster performance quantities including thrust, and discharge current, as well as several component efficiencies and centerline plasma properties. The model is found to yield converged solutions at all conditions, with large 10 kHzrange oscillations and performance trends with voltage and flow rate similar to experiment. The model under-predicts the thrust by 15-25% and over-predicts the discharge current by 20% on average compared to experiments at the same discharge voltage and mass flow rate. This performance discrepancy is due to lower beam utilization, mass utilization, and divergence efficiency than experiment, resulting from high Hall parameters in the acceleration region, which lead to a protracted ion acceleration region. The physical processes underlying this result are discussed in the context of future data-driven modeling efforts.
An ongoing modification is described of a large vacuum chamber to accommodate the ignition of an arcjet hydrazine thruster while maintaining a vacuum level of 1 x 10(exp -5) torr or less. The vacuum facility consists of a 20 ft stainless steel vacuum tank with an internal LN2 shroud, four 35 in. cryopumps and an 8 in. turbopump. To maintain a vacuum level of 1 x 10(exp -5) torr or less, 900 sq ft of liquid helium (LHe) shroud surface was installed to maintain the vacuum level and pumping requirements. A vacuum level of 1 x 10(exp -5) torr or less will allow the hydrazine thrust to exit the thruster nozzle and radiate into a space type environment so that the plume flow field can be analyzed and compared to the analytical model density distribution profile. Some other arcjet thruster characteristics measured are the electromagnetic interference (EMI) and exhaust contamination. This data is used to evaluate if the arcjet thruster with its high specific impulse in comparison to current chemical propulsion thruster can be used for the next generation of communication satellites.
Relationships among polarimetric backscattering coefficients are derived from the viewpoint of symmetry groups. For both reciprocal and non-reciprocal media, symmetry encountered in remote sensing due to reflection, rotation, azimuthal, and centrical symmetry groups is considered. The derived properties are general and valid to all scattering mechanisms, including volume and surface scatterings and their interactions, in a given symmetrical configuration. The scattering coefficients calculated from theoretical models for layer random media and rough surfaces are shown to obey the symmetry relations. Use of symmetry properties in remote sensing of structural and environmental responses of scattering media is also discussed. Orientations of spheroidal scatterers described by spherical, uniform, planophile, plagiothile, erectophile, and extremophile distributions are considered to derive their polarimetric backscattering characteristics. These distributions can be identified from the observed scattering coefficients by comparison with theoretical symmetry calculations. A new parameter is then defined to study scattering structures in geophysical media. Observations from polarimetric data acquired by the Jet Propulsion Laboratory airborne synthetic aperture radar over forests, sea ice, and sea surface are presented. Experimental evidences of the symmetry relationships are shown and their use in polarimetric remote sensing is illustrated. For forests, the coniferous forest in Mt. Shasta area (California) and mixed forest near Presque Isle (Maine) exhibit characteristics of the centrical symmetry at C-band. For sea ice in the Beaufort Sea, multi-year sea ice has a cross-polarized ratio e close to e(sub 0), calculated from symmetry, due to the randomness in the scattering structure. First-year sea ice has e much smaller than e(sub 0) due to the preferential alignment of the columnar structure of the ice. From polarimetric data of a sea surface in the Bering Sea, it is observed that e and e(sub 0) are increasing with incident angle and e is greater than e(sub 0) at L-band because of the directional feature of sea surface waves. Symmetry properties of geophysical media can also be used to calibrate polarimetric radars.
Polarimetric remote sensing of structures in geophysical media is studied in this paper based on their symmetry properties. Orientations of spheroidal scatterers described by spherical, uniform, planophile, plagiothile, erectophile, and extremophile distributions are considered to derive their polarimetric backscattering characteristics. These distributions can be identified from the observed scattering coefficients by comparison with theoretical symmetry calculations. A new parameter is defined to study scattering structures in geophysical media. Experimental observations from polarimetric data acquired by the Jet Propulsion Laboratory airborne synthetic aperture radar over forests, sea ice, and sea surface are presented to illustrate the use of symmetry properties. For forests, the coniferous forest in Mount Shasta area and mixed forests neir Presque Isle show evidence of the centrical symmetry at C band. In sea ice from the Beaufort Sea, multiyear sea ice has a cross-polarized ratio e close to e(sub 0), calculated from symmetry, due to the randomness in the scattering structure. For first-year sea ice, e is much smaller than e(sub 0) as a result of preferential alignment of the columnar structure of the ice. From polarimetric data of a sea surface in the Bering sea, it is observed that e and e(sub 0) are increasing with incident angle and e is greater than e(sub 0) at L band because of the directional feature of sea surface waves. Use of symmetry properties of geophysical media for polarimetric radar calibration is also suggested.
GFSSP stands for Generalized Fluid System Simulation Program. It is a general-purpose computer program to compute pressure, temperature and flow distribution in a flow network. GFSSP calculates pressure, temperature, and concentrations at nodes and calculates flow rates through branches. It was primarily developed to analyze Internal Flow Analysis of a Turbopump Transient Flow Analysis of a Propulsion System. GFSSP development started in 1994 with an objective to provide a generalized and easy to use flow analysis tool for thermo-fluid systems.
Under the Mars Transportation Assessment Study, NASA and DOE are performing analyses and generating concepts for crewed Nuclear Electric Propulsion (NEP) missions to Mars. This paper presents the results of trade studies and concept development for the nuclear electric power system, consisting of the fission reactor, radiation shielding, power conversion, heat rejection and power management & distribution (PMAD). The nuclear power team completed trade studies to evaluate different reactor and power conversion technologies and developed preliminary concepts for the crew shielding, waste heat radiators, and PMAD. The initial results suggest that a modified terrestrial microreactor combined with supercritical CO2 Brayton conversion could be used to perform the crew and cargo missions with satisfactory performance and modest risk.
In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.
This presentation focuses on nearfield airborne pressure signatures from the Lift and Nozzle Change Effect on Tail Shocks (LaNCETS) flight test experiment. The primary motivation for nearfield probing in the supersonic regime is to measure the shock structure of aircraft in an ongoing effort to overcome the overland sonic boom barrier for commercial supersonic transportation. LaNCETS provides the opportunity to investigate lift distribution and engine plume effects. During Phase 1 flight testing an F-15B was used to probe the F-15 LaNCETS aircraft in order to validate CFD and pre-flight prediction tools. A total of 29 probings were taken at 40,000 ft. altitude at Machs 1.2, 1.4 and 1.6. LaNCETS Phase 1 flight data are presented as a detailed pressure signature superimposed over a picture of the LaNCETS aircraft. The attenuation of the Inlet-Canard shocks with distance as well as its forward propagation and the coalescence of the noseboom shock are illustrated. A detailed CFD study on a simplified LaNCETS aircraft jet nozzle was performed providing the ability to more accurately capture the shocks from the propulsion system and emphasizing how under- and over-expanding the nozzle affects the existence of shock trains inside the jet plume. With Phase 1 being a success preparations are being made to move forward to Phase 2. Phase 2 will fly similar flight conditions, but this time changing the aircraft's lift distribution by biasing the canard positions, and changing the plume shape by under- and over-expanding the nozzle. Nearfield probing will again be completed in the same manner as in Phase 1. An additional presentation focuses on LaNCETS CFD solution methodology. Discussions highlight grid preprocessing, grid shearing and stretching, flow solving and contour plots. Efforts are underway to better capture the flow features via grid modification and flow solution methodology, which will help to achieve better agreement with flight data. An included CD-ROM provides animations of the nearfield probing procedure and of real data from one of the probings integrated with GPS positional and velocity data. An additional in-flight video from the rear seat of the probing aircraft is also provided.
Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.
Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.
Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol (Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.
A highly-reliable avionics suite has been designed for an Entry Research Vehicle. The autonomous spacecraft would be deployed from the Space Shuttle Orbiter and perform a variety of aerodynamic and propulsive maneuvers which may be required for future space transportation system vehicles. The flight electronics consist of a central fault-tolerant processor, which is resilient to all first failures, reliably cross-strapped to redundant and distributed sets of sensors and effectors. This paper describes the preliminary design and analysis of the architecture which resulted from a fifteen month study by the Charles Stark Draper Laboratory for the NASA Langley Research Center. After a brief introduction to the design task, the architecture of the central flight computer and its interface to the vehicle are discussed. Following this, the method and results of the baseline reliability study for the avionic suite are presented.
An experimental Aerodynamic and Aero-Acoustic loads data base was obtained at transonic Mach numbers for the Space Shuttle Launch Vehicle configured with the ASRM Solid Rocket Boosters as an increment to the current flight configuration (RSRB). These data were obtained during transonic wind tunnel tests (IA 613A) conducted in the Arnold Engineering Development Center 16-Foot transonic propulsion wind tunnel from March 27, 1991 through April 12, 1991. This test is the first of a series of two tests covering the Mach range from 0.6 to 3.5. Steady state surface static and fluctuating pressure distributions over the Orbiter, External Tank and Solid Rocket Boosters of the Shuttle Integrated Vehicle were measured. Total Orbiter forces, Wing forces and Elevon hinge moments were directly measured as well from force balances. Two configurations of Solid Rocket Boosters were tested, the Redesigned Solid Rocket Booster (RSRB) and the Advanced Solid Rocket Motor (ASRM). The effects of the position (i.e., top, bottom, top and bottom) of the Integrated Electronics Assembly (IEA) box, mounted on the SRB attach ring, were obtained on the ASRM configured model. These data were obtained with and without Solid Plume Simulators which, when used, matched as close as possible the flight derived pressures on the Orbiter and External Tank base. Data were obtained at Mach numbers ranging from 0.6 to 1.55 at a Unit Reynolds Number of 2.5 million per foot through model angles of attack from -8 to +4 degrees at sideslip angles of 0, +4 and -4 degrees.
An experimental Aerodynamic and Aero-Acoustic loads data base was obtained at transonic Mach numbers for the Space Shuttle Launch Vehicle configured with the ASRM Solid Rocket Boosters as an increment to the current flight configuration (RSRB). These data were obtained during transonic wind tunnel tests (IA 613A) conducted in the Arnold Engineering Development Center 16-Foot transonic propulsion wind tunnel from March 27, 1991 through April 12, 1991. This test is the first of a series of two tests covering the Mach range from 0.6 to 3.5. Steady state surface static and fluctuating pressure distributions over the Orbiter, External Tank and Solid Rocket Boosters of the Shuttle Integrated Vehicle were measured. Total Orbiter forces, Wing forces and Elevon hinge moments were directly measured as well from force balances. Two configurations of Solid Rocket Boosters were tested, the Redesigned Solid Rocket Booster (RSRB) and the Advanced Solid Rocket Motor (ASRM). The effects of the position (i.e. top, bottom, top and bottom) of the Integrated Electronics Assembly (IEA) box, mounted on the SRB attach ring, were obtained on the ASRM configured model. These data were obtained with and without Solid Plume Simulators which, when used, matched as close as possible the flight derived pressures on the Orbiter and External Tank base. Data were obtained at Mach numbers ranging from 0.6 to 1.55 at a Unit Reynolds Number of 2.5 million per foot through model angles of attack from -8 to +4 degrees at sideslip angles of 0, +4 and -4 degrees.