Results for “Domain wall motion” — Page 3

NASA NTRS2013

Constraints on Decreases in Eta Carinae's Mass-loss from 3D Hydrodynamic Simulations of Its Binary Colliding Winds

Recent work suggests that the mass-loss rate of the primary star Eta-A in the massive colliding wind binary Eta Carinae dropped by a factor of 2-3 between 1999 and 2010. We present result from large- (+/- 1545 au) and small- (+/- 155 au) domain, 3D smoothed particle hydrodynamics (SPH) simulations of Eta Car's colliding winds for three Eta-A mass-loss rates ( (dot-M(sub Eta-A) = 2.4, 4.8 and 8.5 × 10(exp −4) M(solar)/ yr), investigating the effects on the dynamics of the binary wind-wind collision (WWC). These simulations include orbital motion, optically thin radiative cooling and radiative forces. We find that dot-M Eta-A greatly affects the time-dependent hydrodynamics at all spatial scales investigated. The simulations also show that the post-shock wind of the companion star Eta-B switches from the adiabatic to the radiative-cooling regime during periastron passage (Phi approx.= 0.985-1.02). This switchover starts later and ends earlier the lower the value of dot-M Eta-A and is caused by the encroachment of the wind of Eta-A into the acceleration zone of Eta-B's wind, plus radiative inhibition of Eta-B's wind by Eta-A. The SPH simulations together with 1D radiative transfer models of Eta-A's spectra reveal that a factor of 2 or more drop in dot-M EtaA should lead to substantial changes in numerous multiwavelength observables. Recent observations are not fully consistent with the model predictions, indicating that any drop in dot- M Eta-A was likely by a factor of approx. < 2 and occurred after 2004. We speculate that most of the recent observed changes in Eta Car are due to a small increase in the WWC opening angle that produces significant effects because our line of sight to the system lies close to the dense walls of the WWC zone. A modest decrease in dot-M Eta-A may be responsible, but changes in the wind/stellar parameter of Eta-B, while less likely, cannot yet be fully ruled out. We suggest observations during Eta-Car's next periastron in 2014 to further test for decreases in dot-M Eta-A. If dot-M Eta-A is declining and continues to do so, the 2014 X-ray minimum should be even shorter than that of 2009.

Eta Carinae↗

NASA NTRS2016

Applied Time Domain Stability Margin Assessment for Nonlinear Time-Varying Systems

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.

Kiefer, J. M.↗