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The use of adaptive system to stabilize a launch vehicle with sloshable fuel is discussed. The adaptive system is based on a laser sensor to measure fluid displacement in the tank, a recursive-least-squares estimator to assess the natural frequency of the sloshing fuel, and a linear filter to stabilize the unstable fuel slosh. The method is found to be promising for a pitch-plane, single pendulum model.
Slosh dynamics pose a stability concern for human-rated launch vehicles during ascent. Historical perspectives on the treatment of slosh dynamics, newly developed rules of thumb, the utility of flight data, and methods for analyzing and dispositioning slosh instability risks should be considered when linear stability margins are lower than typically accepted for human-rated systems.
Structural stability can be an important consideration in the design of large composite shell structures and therefore it is important to understand the buckling response of such structures. It is well known that geometric imperfections can significantly influence the buckling response of such structures by causing the buckling loads to be significantly lower than the theoretical buckling load of a geometrically perfect shell structure. Results are presented of an analytical study on the buckling imperfection sensitivity of large-scale conical sandwich structures for launch vehicles. In particular, representative structures from the Space Launch System launch-vehicle development activities will be considered. The study considered composite sandwich conical structures with multiple sandwich core thicknesses and facesheet layups consisting of tape and fabric composite layups. The results of this analytical study indicate that there is conservatism in the NASA current buckling knockdown factor of 0.33 for conical shell structures. Therefore, it is suggested that the buckling response of composite sandwich cones be further investigated through buckling tests and analytical predictions to potentially revise the buckling design recommendations for conical composite structures.
Feasibility of manned participation in control of large launch vehicle
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Dynamic load environment and stability of launch vehicle subject to atmospheric disturbances and inflight winds
A numerical study of the aeroelastic stability of launch vehicles in transonic flight is performed. The unsteady aerodynanic flowfield about the vehicle is simulated using the three dimensional Reynolds-Averaged Navier-Stokes equations with the account for turbulent mixing done by a two-layer algebraic eddy viscosity model. The structural-dynamic formulation considers free-free flexural vibration of an elongated beam with variable properties and the equations are cast in modal form. The two sets of equations are integrated simultaneously in time, after a initial perturbation, to ascertain the aeroelastic stability of a given configuration. The method propossed is described in detail, and results that illustrate its application are presented.
Launch vehicle flight control system and relation to stability requirements and dynamic responses
Transonic aerodynamic characteristics of two-stage fin-stabilized rocket launch vehicle in combination with winged spacecraft
Application of quadratic optimal control, least squares state, and parameter estimation to stability and control of flexible launch vehicle
An investigation was made to determine the dynamic stability characteristics of a 0.015-scale model of the space shuttle launch vehicle at supersonic speeds. These tests were made at angles of attack from -10 deg to 10 deg at Mach numbers of 2.00, 2.86, 3.96, and 4.63. The complete launch vehicle, consisting of the orbiter, external tank, and solid rocket boosters, has positive damping in pitch, roll, and yaw over the angle-of-attack and Mach number range. The orbiter external tank configuration has a region of negative angles pitch damping for small negative of attack at a Mach number of 2.00. At all other test conditions, the orbiter external tank configuration has positive damping about all three axes.
Digital polynomial and adaptive feedback control system techniques for large launch vehicle guidance, stability, and control
A numerical study of the aeroelastic stability of typical launch vehicle configurations in transonic flight is performed. Recent computational fluid dynamics techniques are used to simulate the transonic aerodynamic flow fields, as opposed to relying on experimental data for the unsteady aerodynamic pressures. The flow solver is coupled to an appropriate structural representation of the vehicle. The aerodynamic formulation is based on the thin layer approximation to the Reynolds-Averaged Navier-Stokes equations, where the account for turbulent mixing is done by the two-layer Baldwin and Lomax algebraic eddy viscosity model. The structural-dynamic equations are developed considering free-free flexural vibration of an elongated beam with variable properties and are cast in modal form. Aeroelastic analyses are performed by integrating simultaneously in the two sets of equations. By tracing the growth or decay of a perturbed oscillation, the aeroelastic stability of a given constant configuration can be ascertained. The method is described in detail, and results that indicate its application are presented. Applications include some validation cases for the algorithm developed, as well as the study of configurations known to have presented flutter programs in the past.
Adaptive control systems for stabilizing structural bending modes of Saturn V launch vehicle
This publication presents the control requirements, the details of the designed Flight Control Augmentor's (FCA's), the static stability and dynamic stability wind tunnel test programs, the static stability and control analyses, the dynamic stability characteristics of the experimental Launch Vehicle (LV) with the designed FCA's, and a consideration of the elastic vehicle. Dramatic improvements in flight stability have been realized with all the FCA designs; these ranged from 41 percent to 72 percent achieved by the blunt TE design. The control analysis showed that control increased 110 percent with only 3 degrees of FCA deflection. The dynamic stability results showed improvements with all FCA designs tested at all Mach numbers tested. The blunt TE FCA's had the best overall dynamic stability results. Since the lowest elastic vehicle frequency must be well separated from that of the control system, the significant frequencies and modes of vibration have been identified, and the response spectra compared for the experimental LV in both the conventional and the aft cg configuration. Although the dynamic response was 150 percent greater in the aft cg configuration, the lowest bending mode frequency decreased by only 2.8 percent.
An investigation has been conducted to determine the subsonic and transonic dynamic stability characteristics of a 0.015 scale model of the space shuttle launch vehicle. These tests were conducted in the Langley 8-foot transonic pressure tunnel over a Mach number range from 0.3 to 1.2. Forced oscillation equipment was used to determine the damping characteristics of several configurations about all three axes. The test results show that the model exhibited positive damping in pitch except at the highest Mach number (1.2) where there was a region of negative damping at 2 deg angle of attack. The yawing oscillation tests show that the model exhibited nonlinearities and negative damping at Mach numbers of 0.3 and 0.6. The model exhibited positive roll damping throughout the test angle of attack and Mach range.
Impedance testing for flight control system parameters in studies of launch vehicle dynamic stability
The baseline stability margins for NASA's Space Launch System (SLS) launch vehicle were generated via the classical approach of linearizing the system equations of motion and determining the gain and phase margins from the resulting frequency domain model. To improve the fidelity of the classical methods, the linear frequency domain approach can be extended by replacing static, memoryless nonlinearities with describing functions. This technique, however, does not address the time varying nature of the dynamics of a launch vehicle in flight. An alternative technique for the evaluation of the stability of the nonlinear launch vehicle dynamics along its trajectory is to incrementally adjust the gain and/or time delay in the time domain simulation until the system exhibits unstable behavior. This technique has the added benefit of providing a direct comparison between the time domain and frequency domain tools in support of simulation validation. This technique was implemented by using the Stability Aerospace Vehicle Analysis Tool (SAVANT) computer simulation to evaluate the stability of the SLS system with the Adaptive Augmenting Control (AAC) active and inactive along its ascent trajectory. The gains for which the vehicle maintains apparent time-domain stability defines the gain margins, and the time delay similarly defines the phase margin. This method of extracting the control stability margins from the time-domain simulation is relatively straightforward and the resultant margins can be compared to the linearized system results. The sections herein describe the techniques employed to extract the time-domain margins, compare the results between these nonlinear and the linear methods, and provide explanations for observed discrepancies. The SLS ascent trajectory was simulated with SAVANT and the classical linear stability margins were evaluated at one second intervals. The linear analysis was performed with the AAC algorithm disabled to attain baseline stability margins. At each time point, the system was linearized about the current operating point using Simulink's built-in solver. Each linearized system in time was evaluated for its rigid-body gain margin (high frequency gain margin), rigid-body phase margin, and aero gain margin (low frequency gain margin) for each control axis. Using the stability margins derived from the baseline linearization approach, the time domain derived stability margins were determined by executing time domain simulations in which axis-specific incremental gain and phase adjustments were made to the nominal system about the expected neutral stability point at specific flight times. The baseline stability margin time histories were used to shift the system gain to various values around the zero margin point such that a precise amount of expected gain margin was maintained throughout flight. When assessing the gain margins, the gain was applied starting at the time point under consideration, thereafter following the variation in the margin found in the linear analysis. When assessing the rigid-body phase margin, a constant time delay was applied to the system starting at the time point under consideration. If the baseline stability margins were correctly determined via the linear analysis, the time domain simulation results should contain unstable behavior at certain gain and phase values. Examples will be shown from repeated simulations with variable added gain and phase lag. Faithfulness of margins calculated from the linear analysis to the nonlinear system will be demonstrated.