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Lee, Allan Y.

Publications and source records attributed to Lee, Allan Y..

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Estimation of Enceladus Plume Density Using Cassini Flight Data

The Cassini spacecraft was launched on October 15, 1997 by a Titan 4B launch vehicle. After an interplanetary cruise of almost seven years, it arrived at Saturn on June 30, 2004. In 2005, Cassini completed three flybys of Enceladus, a small, icy satellite of Saturn. Observations made during these flybys confirmed the existence of water vapor plumes in the south polar region of Enceladus. Five additional low-altitude flybys of Enceladus were successfully executed in 2008-9 to better characterize these watery plumes. During some of these Enceladus flybys, the spacecraft attitude was controlled by a set of three reaction wheels. When the disturbance torque imparted on the spacecraft was predicted to exceed the control authority of the reaction wheels, thrusters were used to control the spacecraft attitude. Using telemetry data of reaction wheel rates or thruster on-times collected from four low-altitude Enceladus flybys (in 2008-10), one can reconstruct the time histories of the Enceladus plume jet density. The 1 sigma uncertainty of the estimated density is 5.9-6.7% (depending on the density estimation methodology employed). These plume density estimates could be used to confirm measurements made by other onboard science instruments and to support the modeling of Enceladus plume jets.

Wang, Eric K.↗
NASA NTRS2010

Preliminary Characterization of the Altair Lunar Lander Slosh Dynamics and Some Implications for the Thrust Vector Control Design

This paper describes a conceptual design of the Thrust Vector Control (TVC) system and preliminary modeling of propellant slosh, for the Altair Lunar Lander. Altair is a vehicle element of the NASA Constellation Program aimed at returning humans to the moon. Guidance, Navigation, and Control (GN&C) is the measurement and control of spacecraft position, velocity, and attitude in support of mission objectives. One key GN&C function is the commanding of effectors that control attitude and impart delta V on the vehicle, utilizing both reaction control system (RCS) thrusters and throttling and TVC gimbaling of the vehicle main engine. Both the Altair descent and ascent modules carry fuel tanks. During thrusting maneuvers, the sloshing of liquid fuels in partially filled tanks can interact with the controlled system in such a way as to cause the overall system to be unstable. These fuel tanks must be properly placed, relative to the spacecraft's c.m., to avoid any unstable interactions. Following this will be a discussion of propellant slosh modeling work performed for the present vehicle configuration, including slosh frequency and participatory fluid mass predictions. Knowing the range of slosh mode frequencies over mission phases, the TVC bandwidth must be carefully selected so as not to excite the slosh modes at those frequencies. The likely need to increase the damping factor of slosh modes via baffles will also be discussed. To conclude, a discussion of operations procedures aimed at minimizing TVC-slosh interactions will be given.

Lee, Allan Y.↗
NASA NTRS2010

Estimation and Modeling of Enceladus Plume Jet Density Using Reaction Wheel Control Data

The Cassini spacecraft was launched on October 15, 1997 by a Titan 4B launch vehicle. After an interplanetary cruise of almost seven years, it arrived at Saturn on June 30, 2004. In 2005, Cassini completed three flybys of Enceladus, a small, icy satellite of Saturn. Observations made during these flybys confirmed the existence of a water vapor plume in the south polar region of Enceladus. Five additional low-altitude flybys of Enceladus were successfully executed in 2008-9 to better characterize these watery plumes. The first of these flybys was the 50-km Enceladus-3 (E3) flyby executed on March 12, 2008. During the E3 flyby, the spacecraft attitude was controlled by a set of three reaction wheels. During the flyby, multiple plume jets imparted disturbance torque on the spacecraft resulting in small but visible attitude control errors. Using the known and unique transfer function between the disturbance torque and the attitude control error, the collected attitude control error telemetry could be used to estimate the disturbance torque. The effectiveness of this methodology is confirmed using the E3 telemetry data. Given good estimates of spacecraft's projected area, center of pressure location, and spacecraft velocity, the time history of the Enceladus plume density is reconstructed accordingly. The 1 sigma uncertainty of the estimated density is 7.7%. Next, we modeled the density due to each plume jet as a function of both the radial and angular distances of the spacecraft from the plume source. We also conjecture that the total plume density experienced by the spacecraft is the sum of the component plume densities. By comparing the time history of the reconstructed E3 plume density with that predicted by the plume model, values of the plume model parameters are determined. Results obtained are compared with those determined by other Cassini science instruments.

Lee, Allan Y.↗
NASA NTRS2010

Preliminary Characterizations of Altair Lunar Lander Slosh Dynamics and Some Implications for TVC Design

During thrust maneuvers, the sloshing of fuel in partially filled tanks could interact with the controlled system in such a way as to cause the overall system to be unstable. This failure mode could be a result of poor coordination between systems engineers of Structures, Propulsion, GN&C, Mission Operations, and other subsystems. Attentions to the following is a minimum: Placements of fuel tanks, Tank shapes and baffle designs, Separation of TVC BW from slosh mode frequencies, Adequacy of excursion range of engine gimbal actuators in all engine burns, BW of sensors (e.g., gyroscopes) and actuators (e.g., engine gimbal), Structural frequencies of spacecraft and engine mounts, Prediction of S/C's c.m. location, canting of gimbal null axis, others. Check overall TVC performance via validated simulation test bed. Modeling fuel slosh during spacecraft thrusting maneuvers • Placement of fuel tanks to guarantee stable interactions between fuel slosh mode and the S/C rigid-body mode • Estimation of slosh frequencies (as a function of mission phases): – Estimation of slosh mode damping • Some implications for Thrust Vector Control design: – Selection of TVC controller bandwidth – Adequacy of the excursion range of engine gimbal actuator • TVC system design: Complex Interactions between GN&C, Propulsion, Structure, and Other Subsystems

Thrust vector control↗
NASA NTRS2010

Preliminary Design of the Guidance, Navigation, and Control System of the Altair Lunar Lander

Guidance, Navigation, and Control (GN&C) is the measurement and control of spacecraft position, velocity, and attitude in support of mission objectives. This paper provides an overview of a preliminary design of the GN&C system of the Lunar Lander Altair. Key functions performed by the GN&C system in various mission phases will first be described. A set of placeholder GN&C sensors that is needed to support these functions is next described. To meet Crew safety requirements, there must be high degrees of redundancy in the selected sensor configuration. Two sets of thrusters, one on the Ascent Module (AM) and the other on the Descent Module (DM), will be used by the GN&C system. The DM thrusters will be used, among other purposes, to perform course correction burns during the Trans-lunar Coast. The AM thrusters will be used, among other purposes, to perform precise angular and translational controls of the ascent module in order to dock the ascent module with Orion. Navigation is the process of measurement and control of the spacecraft's "state" (both the position and velocity vectors of the spacecraft). Tracking data from the Earth-Based Ground System (tracking antennas) as well as data from onboard optical sensors will be used to estimate the vehicle state. A driving navigation requirement is to land Altair on the Moon with a landing accuracy that is better than 1 km (radial 95%). Preliminary performance of the Altair GN&C design, relative to this and other navigation requirements, will be given. Guidance is the onboard process that uses the estimated state vector, crew inputs, and pre-computed reference trajectories to guide both the rotational and the translational motions of the spacecraft during powered flight phases. Design objectives of reference trajectories for various mission phases vary. For example, the reference trajectory for the descent "approach" phase (the last 3-4 minutes before touchdown) will sacrifice fuel utilization efficiency in order to provide landing site visibility for both the crew and the terrain hazard detection sensor system. One output of Guidance is the steering angle commands sent to the 2 degree-of-freedom (dof) gimbal actuation system of the descent engine. The engine gimbal actuation system is controlled by a Thrust Vector Control algorithm that is designed taking into account the large quantities of sloshing liquids in tanks mounted on Altair. In this early design phase of Altair, the GN&C system is described only briefly in this paper and the emphasis is on the GN&C architecture (that is still evolving). Multiple companion papers will provide details that are related to navigation, optical navigation, guidance, fuel sloshing, rendezvous and docking, machine-pilot interactions, and others. The similarities and differences of GN&C designs for Lunar and Mars landers are briefly compared.

Lee, Allan Y.↗
NASA NTRS2010

Optical Navigation Plan and Strategy for the Lunar Lander Altair

This paper reviews the currently planned Altair Optical Navigation (OpNav) system. The discussion includes description of the OpNav camera manifest. The Altair OpNav plan envisions one, OpNav camera assembly, with perhaps a functional backup that includes a wide angle-imager (of 40 deg to 60 deg field of view - FOV), and a narrow angle imager (of 1 to 3 deg FOV) co-mounted on a 2-degree-of-freedom gimbal. Both imagers are assumed to be relatively wide aperture and large dynamic range to provide excellent short-exposure images at mid-latitudes, and adequate images of longer-exposure near the poles. Landmark modeling and tracking methodology is discussed, including the stereophotoclinometry method assumed to be used to obtain high-accuracy terrain maps at lunar landing sites of 1 - 2 m, and 50 - 100 m elsewhere, using the images expected to be obtained from the Lunar Reconnaissance Orbiter (LRO). Characteristics of the OpNav navigation system are discussed and architecture and results from landing simulations presented, showing expected landing accuracies of better than 10m.

TAG↗
NASA NTRS2010

Estimation and Modeling of Enceladus Plume Jet Density Using Reaction Wheel Control Data

The Cassini spacecraft was launched on October 15, 1997 by a Titan 4B launch vehicle. After an interplanetary cruise of almost seven years, it arrived at Saturn on June 30, 2004. In 2005, Cassini completed three flybys of Enceladus, a small, icy satellite of Saturn. Observations made during these flybys confirmed the existence of a water vapor plume in the south polar region of Enceladus. Five additional low-altitude flybys of Enceladus were successfully executed in 2008-9 to better characterize these watery plumes. The first of these flybys was the 50-km Enceladus-3 (E3) flyby executed on March 12, 2008. During the E3 flyby, the spacecraft attitude was controlled by a set of three reaction wheels. During the flyby, multiple plume jets imparted disturbance torque on the spacecraft resulting in small but visible attitude control errors. Using the known and unique transfer function between the disturbance torque and the attitude control error, the collected attitude control error telemetry could be used to estimate the disturbance torque. The effectiveness of this methodology is confirmed using the E3 telemetry data. Given good estimates of spacecraft's projected area, center of pressure location, and spacecraft velocity, the time history of the Enceladus plume density is reconstructed accordingly. The 1-sigma uncertainty of the estimated density is 7.7%. Next, we modeled the density due to each plume jet as a function of both the radial and angular distances of the spacecraft from the plume source. We also conjecture that the total plume density experienced by the spacecraft is the sum of the component plume densities. By comparing the time history of the reconstructed E3 plume density with that predicted by the plume model, values of the plume model parameters are determined. Results obtained are compared with those determined by other Cassini science instruments.

Lee, Allan Y.↗
NASA NTRS2009

Importance of Model Simulations in Cassini In-Flight Mission Events

Simulation environments have been an integral part of Cassini's heritage. From the time of flight software development and testing to the beginning of the spacecraft's extended mission operations, both softsim and hardware-in-the-loop testbeds have played vital roles in verifying and validating key mission events. Satellite flybys and mission-critical events have established the need to model Titan's atmospheric torque, Enceladus' plume density, and other key parametric spacecraft environments. This paper will focus on enhancements to Cassini's Flight Software Development System (FSDS) and Integrated Test Laboratory (ITL) to model key event attributes which establish valid test environments and ensure safe spacecraft operability. Comparisons between simulated to in-flight data are presented which substantiate model validity.

FSDS↗
NASA NTRS2008

Pointing Stability Performance of the Cassini Spacecraft

Twelve scientific instruments onboard the Cassini spacecraft depend on the accurate pointing capabilities of the spacecraft to return data critical to the success of the mission and to improving our understanding of Saturn. Throughout the seven year interplanetary cruise to Saturn and the four year prime mission, the control of the Cassini spacecraft is achieved by employing either the Reaction Control System (RCS) composed of a set of eight thrusters or the Reaction Wheel Assembly (RWA) made up of four reaction wheels, only three of which are active at a given time. The operations of Cassini imaging instruments (such as the Narrow Angle Camera) require a high level of spacecraft pointing stability in order to minimize the distortion and smearing of the image during the exposure time. In designing the Cassini attitude control system, a pointing stability performance metric that considered the frequency contents of the disturbance sources was employed. The flight performance of the Cassini pointing stability, achieved with a set of three reaction wheels or RCS thrusters, is summarized in this paper.

Lee, Allan Y.↗
NASA NTRS2006

In flight estimations of Cassini spacecraft inertia tensor and thruster magnitude

This paper describes two methods used by the Cassini Attitude Control team to determine these key parameters and how flight telemetry was used to estimate them. The method for estimating the spacecraft inertia tensor exploits the conservation of angular momentum during spacecraft slews under reaction wheel control.

inertia properties↗
NASA NTRS1996

A Variable Stability Test Vehicle for ITS Applications

A variable stability test bed is under development for the National Highway Traffic Safety Administration (NHTSA). The Variable Dynamic Testbed Vehicle (VDTV) is being designed for research and testing of advanced collision warning and avoidance technologies being developed by industry and most likely being made available to consumers in the near future.

technologies↗
NASA NTRS1995

Performance of Driver-Vehicle in Aborted Lane Change Maneuvers

A 'lane change crash' is defined as a family of collisions that occurred when a driver attempts to change lane and strikes or is struck by a vehicle in the adjacent lane. One type of maneuver that is commonly used to avert a lane change crash involved aborting the intended lane change, and returning the vehicle to the original lane of the subject vehicle.

Aborted Lane Change↗
NASA NTRS1994

Synthesis of minimum-time feedback laws for dynamic systems using neural networks

The paper presents the synthesis of neural network based feedback laws for dynamic systems using the computed optimal and time histories of the state and control variables. The efficacy of the proposed approach has been successfully demonstrated on a minimum time orbit injection problem. If the method is found to be effective to real life problems with many state and control variables, it can used for a variety of guidance and control problems.

TRT-THEORETICAL↗
NASA NTRS1993

Component modes damping assignment methodology for articulated, multiflexible body structures

To simulate the dynamical motion of articulated, multiflexible body structures, one can use multibody simulation packages such as DISCOS. To this end, one must supply appropriate reduced-order models for all of the flexible components involved. The component modes projection and assembly model reduction (COMPARE) methodology is one way to construct these reduced-order component models, which when reassembled capture important system input-to-output mapping of the full-order model at multiple system configurations of interest. In conjunction, we must also supply component damping matrices which when reassembled generate a system damping matrix that has certain desirable properties. The problem of determining the damping factors of components' modes to achieve a given system damping matrix is addressed here. To this end, we must establish from first principles a matrix-algebraic relation between the system's modal damping matrix and the components' modal damping matrices. An unconstrained/constrained optimization problem can then be formulated to determine the component modes' damping factors that best satisfy that matrix-algebraic relation. The effectiveness of the developed methodology, called ModeDamp, has been successfully demonstrated on a high-order, finite element model of the Galileo spacecraft.

Lee, Allan Y.↗