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A coherent Doppler lidar capable of providing accurate velocity and altitude data has been developed and demonstrated for future NASA missions to the solar system bodies requiring precision navigation and controlled soft landing.
NASA's Mars Sample Return campaign will be launching several missions over the next decade that will work together to return rock samples from Mars back to Earth. The Sample Retrieval Lander (SRL) will deliver the Mars Ascent Vehicle and fetch rover to the surface of Mars in 2006. Rock samples collected by the Mars 2020 Perseverance rover, landing in early 2021, will be loaded on the the ascent vehicle to be launched into Mars orbit for retrieval by yet another spacecraft. The Sample Retrieval Lander will be a blunt entry capsule similar to past Mars entry vehicles like Mars Science Laboratory and Viking. The vehicle will fly a guided entry, using a small lift vector produced by a non-zero trim angle of attack to eliminate downrange and crossrange position errors at the point of parachute deploy. This energy and heading management is achieved with a reaction control system (RCS) that directs the bank angle of the vehicle and also minimizes unwanted capsule dynamics. The reaction control system and control design is based on the Mars Science Laboratory and Mars 2020 RCS systems. However, due to packaging constraints, the backshell of this new entry vehicle has a different geometry than those earlier designs. To certify the RCS system for flight the project must characterize the jet plume interactions with the capsule backshell that could impair or significantly augment the RCS control authority. This characterization will be done through a combination of computational fluid dynamics (CFD) analysis and wind tunnel test. Two candidate arrangements of the RCS jets have been identified for the SRL vehicle and are currently under evaluation before final selection. The aero/RCS plume interactions of these candidate configurations have been measured in a supersonic wind tunnel test in NASA Langley's Unitary Plan Wind Tunnel. The test was conducted in the fall of 2020 and data is currently being reduced. An overview of the candidate RCS configurations are presented here with an overview of the wind tunnel model design, jet scaling and scaled nozzle design, and the test matrix. Preliminary CFD runs are presented with an assessment of the predicted plumes and their interaction with the wake flow of the vehicle. The predicted effects of the model sting is provided as well. This high fidelity wind tunnel test is being conducted much earlier in the SRL project than would normally be done. The test was funded as part of a CFD evaluation task funded by NASA's Aerosciences Evaluation and Test Capabilities Project. The objective of the evaluation task was to compare the ability of CFD to predict complex flows with data that can be measured in the Langley Unitary Plan Wind Tunnel. RCS Jet interactions were selected as a type of complex flow that is important to NASA missions. In addition to providing useful data to the SRL project, there was added emphasis on quantifying the accuracy of the CFD predictions and wind tunnel test data. An overview of the uncertainty quantification methodologies for computational and experimental portions of this test is presented.
Ground tests of solid propellant rocket motors have shown that metal-containing propellants produce various amounts of slag (primarily aluminum oxide), which is trapped in the motor case causing a loss of specific impulse. Although not yet definitely established, the presence of a liquid pool of slag also may contribute to nutational instabilities that have been observed with certain spin-stabilized, upper-stage vehicles. Because of the rocket's axial acceleration - absent in the ground tests - estimates of in-flight slag mass have been very uncertain. Yet such estimates are needed to determine the magnitude of the control authority of the systems required for eliminating the instability. A test rig with an eccentrically mounted hemispherical bowl was designed and built that incorporates a follower force that properly aligns the thrust vector along the axis of spin. A program that computes the motion of a point mass in the spinning and precessing bowl was written. Using various rpm, friction factors, and initial starting conditions, plots were generated showing the trace of the point mass around the inside of the fuel tank. The apparatus will be used extensively during the 1990 to 1991 academic year and incorporate future design features such as a variable nutation angle and a film height measuring instrument. Data obtained on the nutational instability characteristics will be used to determine order-of-magnitude estimates of control authority needed to minimize the sloshing effect.
Necessary and sufficient conditions are derived in terms of system parameters and quadratic weighting matrices for two quadratic cost functionals that are defined to be equivalent if they generate the same optimal control law. The derived conditions lie between the conditions of Tanaka and Asai (1971) and those of Kreindler and Hedrick (1970). Sufficient conditions for a vector valued function to attain an infimum are stated.
A numerical simulation of bubble-type vortex breakdown using a unique discrete form of the full 3-D, unsteady incompressible Navier-Stokes equations was performed. The Navier-Stokes equations were written in a vorticity-velocity form and the physical problem was not restricted to axisymmetric flow. The problem was parametized on a Rossby- Reynolds-number basis. Utilization of this parameter duo was shown to dictate the form of the free-field boundary condition specification and allowed control of axial breakdown location within the computational domain. The structure of the breakdown bubble was studied through time evolution plots of planar projected velocity vectors as well as through plots of particle traces and vortex lines. These results compared favorably with previous experimental studies. In addition, profiles of all three velocity components are presented at various axial stations and a Fourier analysis was performed to identify the dominant circumferential modes. The dynamics of the breakdown process were studied through plots of axial variation of rate of change of integrated total energy and rate of change of integrated enstrophy, as well as through contour plots of velocity, vorticity and pressure.
A unique facility has been developed at the NASA Ames Research Center to provide scientists with unusual research opportunities at greater than Earth's gravity. In addition to its use for basic research, this facility will help provide answers to many of the questions posed by proponents of rotating human space vehicles. This paper describes the design and planned use of this facility, the Spaceflight Environmental Simulator. Using an existing 52-foot diameter cylindrical rotating platform design centrifuge, the revised facility design includes the provision of two human habitats for long duration studies of the effects of hypergravity. Up to four humans (per habitat) will be able to live at up to 2 G for as long as one month without stopping the centrifuge. Each habitat, constructed of lightweight honeycomb sandwich panels, is nominally 9 ft high x 11 ft wide x 25 1/2 ft long. A radial positioning system provides for positioning each habitat at a distance of 15 to 21 feet from the centrifuge's axis of rotation to the midpoint of the habitat's interior floor. As centrifugal acceleration changes with rotation rate, a habitat floor-mounted accelerometer signal provides automatic servo controlled adjustment of each habitat's angle of inclination to provide an environment for the habitat's crew and cargo in which the resultant gravity vector is normal to the habitat floor at all times. Design of the habitats and modifications to the centrifuge are complete, and are currently under construction. Design philosophy and operational rationale are presented along with complete descriptions of the facility and its systems.
A procedure has been developed for constructing a statistical model of the altitude-dependent mean wind profile from the historical record of wind measurements at particular locations. The model is constructed by fitting a Markov process, with altitude as the stage variable, to the historical wind data. The wind model, together with the aircraft dynamics and the error characteristics of the navigation system, are incorporated in the design of a state estimator, which gives the minimum variance estimate of the aircraft state and the wind vector. The state and wind estimates are used as inputs to a linear feedback law for guiding the aircraft along the nominal trajectory. An example design of a time-constrained (4D RNAV) descent guidance system is presented, showing tracking accuracy, control activity, and probability of arrival time with and without the wind estimator.
Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulations.Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulatns.
The theory of optimal control for nonscalar-valued performance criteria is discussed. In the space, where the performance criterion attains its value, the relations better than, worse than, not better than, and not worse than are defined by a partial order relation. The notion of optimality splits up into superiority and non-inferiority, because worse than is not the complement of better than, in general. A superior solution is better than every other solution. A noninferior solution is not worse than any other solution. Noninferior solutions have been investigated particularly for vector-valued performance criteria. Superior solutions for non-scalar-valued performance criteria attaining their values in abstract partially ordered spaces are emphasized. The main result is the infimum principle which constitutes necessary conditions for a control to be a superior solution to an optimal control problem.
Development of a design method for including the effects of parameter uncertainties in the design of linear control systems. The approach taken to this problem may be classified as a special case of the stochastic control problem. Thus the formulation is based on the minimization of the expected value of a quadratic performance index defined in terms of the system state vector. The uncertainty in the value of the performance index is the result of the statistical nature of the system parameters rather than a random input signal. It is shown that the expected value of the performance index may be written as a sum of two terms under the assumption of first-order variations of the system state. The first of these terms expresses the nominal performance of the system when the system parameters assume their mean values. The second term represents the effect of the uncertainties on the expected value of the performance index, and is interpreted as an index of system sensitivity.
The problem is studied of determining a stochastic optimal controller for an n-body spacecraft. The approach used in obtaining the stochastic controller involves the application, interpretation, and combination of advanced dynamical principles and the theoretical aspects of modern control theory. The stochastic controller obtained for a complicated model of a spacecraft uses sensor angular measurements associated with the base body to obtain smoothed estimates of the entire state vector, can be easily implemented, and enables system performance to be significantly improved.
Twenty six samples from seven hand specimens, collected from the station 6 boulder at the Apollo 17 landing site, were studied magnetically. The boulder is a breccia consisting of three lithologic units distinguished by their clast population. The direction of magnetization of samples from unit B which is almost devoid of large clasts cluster fairly well after alternating field demagnetization. Samples from unit C which is characterized by abundant large clasts up to 1 m in size do not contain a uniform direction of magnetization but the distribution is not random. Based on these data we propose that the natural remanent magnetization (NRM) in these breccias is the vector sum of two magnetizations, a pre-impact magnetization and a partial thermoremanence acquired during breccia formation. The relative contribution of the two components is controlled by the thermal history of the ejecta, which in turn is determined by its clast population. Depending on the clast population, the NRM can be a total thermoremanence, a partial thermoremanence plus a pre-impact magnetization, or a pre-impact magnetization. This model of thermal overprinting might be applicable to all lunar breccias of medium and higher metamorphic grade.
The identification and explanation of short wavelength antenna interference effects observed in spacecraft plasma wave data have provided an important new method of determining limits on the wavelength, direction of propagation, and Doppler shift of short wavelength electrostatic waves. Using the ISEE-1 wideband electric field data, antenna interference effects have been identified in the ion waves upstream of the earth's bow shock. This identification implies that wavelengths of the upstream ion waves are shorter than the antenna length. The interference effects also provide new measurements of the direction of propagation of the ion waves. The new measurements show that the wave vectors of the ion waves are not parallel to the interplanetary magnetic field (IMF) as previously reported. The direction of propagation does not appear to be controlled by the IMF. In addition, analysis of the Doppler shift of the short wavelength ion waves has provided a measurement of the dispersion relation. The upper limit of the rest frame frequency was found to be on the order of the ion plasma frequency. At this frequency, the wavelength is on the order of a few times the Debye length. The results of this study now provide strong evidence that the ion waves in the upstream region are Doppler-shifted ion acoustic waves. Previously announced in STAR as N83-36328
The activity of the sun can be studied through the measurement of its magnetic field. The measurement of the polarization state of the sunlight in a narrow spectral bandwidth can be related to the magnetic fields strengths and directions over the active sunspots. Measuring the polarization state can be done using the vector magnetograph. The essential component of the vector magnetograph is the polarization modulators. Electro-optical modulators are used as dynamic retarders. KDP (potassium dideuterium phosphate) crystals provide variable retardation which can be controlled by the applied voltage. KDP's have a high contrast ratio but suffer some problems; they require a high voltage and have a limited modulation lifetime. The KDP modulator forms the heart of the polarimeter assembly which is used for carrying out accurate measurements of linear polarization of the sun. It is therefore important to study the optical and electrical behavior of the KDP crystals so that the ultimate goal of making stable electro-optical modulators in the laboratory is achieved. A number of activities were performed in coating and testing the KDP crystals. A summary of these activities is given.
Although our understanding of effects of space flight on human physiology has advanced significantly over the past four decades, the potential contribution of stress at the cellular and gene regulation level is not characterized. The objective of this ground-based study was to evaluate stress gene regulation in cells exposed to altered gravity and environmentally suboptimal conditions. We designed primers to detect message for both the constitutive and inducible forms of the heat shock protein, HSP-70. Applying the reverse transcriptase-polymerase chain reaction (RT-PCR), we probed for HSP-70 message in human acute T-cell leukemia cells, Jurkat, subjected to three types of environmental stressors: (1) altered gravity achieved by centrifugation (hypergravity) and randomization of the gravity vector in rotating bioreactors, (2) serum starvation by culture in medium containing 0.05% serum, and (3) temperature elevation (42 degrees C). Temperature elevation, as the positive control, significantly increased HSP-70 message, while centrifugation and culture in rotating bioreactors did not upregulate heat shock gene expression. We found a fourfold increase in heat shock message in serum-starved cells. Message for the housekeeping genes, actin and cyclophilin, were constant and comparable to unstressed controls for all treatments. We conclude that gravitational perturbations incurred by centrifugal forces, exceeding those characteristic of a Space Shuttle launch (3g), and culture in rotating bioreactors do not upregulate HSP-70 gene expression. In addition, we found RT-PCR useful for evaluating stress in cultured cells. Copyright 2000 Wiley-Liss, Inc.
An online entry guidance algorithm has been developed using a predictor-corrector approach. The algorithm is designed for the Reusable Launch Vehicle (RLV) and is demonstrated by using, the X-33 model. The objective of the design is to handle widely dispersed entry conditions and deliver the vehicle at the Terminal Area Energy Management (TAEM) interface box within an acceptable tolerance and without violating any of the vehicle physical constraints. Combination of several control variables is used in testing the performance and computational requirement of the algorithm. The control variables are the bank angle, angle-of-attack and the time for roll reversal. The bank angle and angle-of-attack profiles are the nominal profiles plus the perturbations in each direction. The initial guess of the bank profile is a 45 degrees bank angle with reversal at 360 seconds from liftoff. A six-element state vector is propagated to the TAEM interface box through the integration of the equations of motion (EOM). Altitude, heading and range errors are computed between the desired and the achieved state at the TAEM interface. These errors are used to correct the initial guess of the control variables. This process is repeated until the errors meet an acceptable level at the TAEM interface. Several numerical optimization methods are used to evaluate the convergent property of the predictor-predictor methodology. Successful results are demonstrated using the X-33 model.
Triana is a single-string spacecraft to be placed in a halo orbit about the sun-earth Ll Lagrangian point. The Attitude Control Subsystem (ACS) hardware includes four reaction wheels, ten thrusters, six coarse sun sensors, a star tracker, and a three-axis Inertial Measuring Unit (IMU). The ACS Safehold design features a gyroless sun-pointing control scheme using only sun sensors and wheels. With this minimum hardware approach, Safehold increases mission reliability in the event of a gyroscope anomaly. In place of the gyroscope rate measurements, Triana Safehold uses wheel tachometers to help provide a scaled estimation of the spacecraft body rate about the sun vector. Since Triana nominally performs momentum management every three months, its accumulated system momentum can reach a significant fraction of the wheel capacity. It is therefore a requirement for Safehold to maintain a sun-pointing attitude even when the spacecraft system momentum is reasonably large. The tachometer sun-line rate estimation enables the controller to bring the spacecraft close to its desired sun-pointing attitude even with reasonably high system momentum and wheel drags. This paper presents the design rationale behind this gyroless controller, stability analysis, and some time-domain simulation results showing performances with various initial conditions. Finally, suggestions for future improvements are briefly discussed.
An enhanced design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented in this paper. It specific-ally addresses the under-determined estimation problem, in which there are more unknown parameters than available sensor measurements. This work builds upon an existing technique for systematically selecting a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. While the existing technique was optimized for open-loop engine operation at a fixed design point, in this paper an alternative formulation is presented that enables the technique to be optimized for an engine operating under closed-loop control throughout the flight envelope. The theoretical Kalman filter mean squared estimation error at a steady-state closed-loop operating point is derived, and the tuner selection approach applied to minimize this error is discussed. A technique for constructing a globally optimal tuning parameter vector, which enables full-envelope application of the technology, is also presented, along with design steps for adjusting the dynamic response of the Kalman filter state estimates. Results from the application of the technique to linear and nonlinear aircraft engine simulations are presented and compared to the conventional approach of tuner selection. The new methodology is shown to yield a significant improvement in on-line Kalman filter estimation accuracy.