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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Detection and Mitigation of Transient Instabilities in Deployable Booms

Deployable space structures offer versatile uses in many space applications, as they can create very large space structures from a single space launch. However, they usually present important dynamical challenges during the critical deployment phase. In this paper, we focus on the dynamical behavior of deployable booms and the important challenge of avoiding collisions between boom’s structural elements or with other parts of the spacecraft, that can potentially have serious consequences. We define this kind of collisions as “transient instabilities” in deployable booms. A new paradigm to tackle these issues is presented in this paper, using techniques from multi-agent/swarm literature like transient instability prevention methods that avoid inter-agent collisions. We have adapted these techniques to deployable booms to guarantee safe deployment of booms and avoid collisions. We also present computational simulations of boom deployment in order to validate our techniques and demonstrate its use for future space missions.

Balas, Mark↗
NASA NTRSDate not supplied

Ascent Aborts 2 Flight, Reconstruction of Structural Dynamics (Couple Loads Transients)

- This work describes the elements of AA2 post-flight data analysis, couple loads analysis, and comparisons of the flight data with the results of analytical methods transiently. - The measured transient responses ranged from rigid body frequencies (zero Hz) to 150 Hz. - The analytical methods consisted of defining and determining all forcing functions, i.e., buffet, aerodynamics, thrusts from the abort motor and the carrier lunch vehicle motor, and the initial conditions at pre-separation. - Mathematical models representing the mechanics of Orion abort is relatively complex because 1) two motors (carrier’s and LAS’s) are operating at the same time at pre-separation, and 2) the separation occurs in atmosphere. - Other challenges consist of determining the aerodynamics with plume-on condition at every millisecond of the flight ranging from transonic to supersonic (i.e., Mach 1.1 to Mach 1.6), and defining the mechanics of separation of LAS from the launch vehicle.

Launch Vehicle↗
NASA NTRS2023

Foreshock Ion Motion Across Discontinuities: Formation of Foreshock Transients

In the ion foreshock, hot flow anomalies (HFAs) and foreshock bubbles (FBs) are two types of foreshock transients that have the strongest fluctuations, which can disturb the magnetosphere-ionosphere system and increase shock acceleration efficiency. They form due to interaction between the foreshock ions and solar wind discontinuities: the direction of the foreshock ion-driven current and whether it decreases or increases the magnetic field strength behind the discontinuity determine whether the transient's formation can be promoted or suppressed. Thus, to predict the HFA and FB formation and forecast their space weather effects, it is necessary to predict the foreshock ion-driven current direction. In this study, we derive analytical equations of foreshock ion velocities within discontinuities to estimate foreshock ion-driven current direction, which provides a quantitative criterion of HFA and FB formation. To validate the criterion, we use Acceleration Reconnection Turbulence & Electrodynamics of Moon's Interaction with the Sun to observe pristine solar wind discontinuities and calculate discontinuity parameters. We use Magnetospheric Multiscale to observe the foreshock ion motion around the discontinuities and show that the data support our model. This study is another step toward a predictive model of HFA and FB formation so that we can forecast their space weather effects at Earth using solar wind observations at lunar orbit or L1.

Terry Z. Liu↗
NASA NTRS2023

Transient Liquefaction on the Lunar or Martian Surface Operational Demonstration

The Cryogenic Fluid In-situ Liquefaction for Landers (CryoFILL) activity has been investigating concepts for the liquefaction of cryogenic fluids produced on the surface of the Moon and Mars. Liquefaction testing of oxygen in a scaled lander tank using an integrated, industrial cryocooler system was completed. The testing covered the determination of the nominal performance operation of the system, constant liquefaction performance, and transient liquefaction performance. The goal of the testing was to demonstrate cryogenic liquefaction operational capabilities on the Lunar and Martian surfaces for landers and In Situ Resource Utilization. The testing met all key performance parameter threshold values including liquefaction rate (demonstrated 1.6 kg/hr compared to threshold of 1.1 kg/hr), number of variables as transient (goal of 3: liquefaction flow, environmental temperature, and cryocooler input power – all demonstrated), and number of fill levels (goal of 3: < 5%, 50%, and 90% - all demonstrated). Key testing results from oxygen liquefaction testing will be discussed including sensitivities provided by the analysis team.

Liquefaction↗
NASA NTRSDate not supplied

Transient Optimization of an Electrified Gas Turbine Engine Using Machine Learning

Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.

Stall Margin↗
NASA NTRSDate not supplied

Transients and Dayside Magnetospheric Interactions

Observations at and deep within the Earth’s dayside magnetosphere provide considerable evidence indicating that the solar wind-magnetosphere interaction is often unsteady. Bursty reconnection resulting in the formation of flux transfer events and transient auroral brightenings is common. Fluctuations in solar wind parameters may trigger some bursts of reconnection, while other bursts may result from intrinsic magnetopause instabilities. Large amplitude solitons often travel along the dayside magnetopause. Deeper within the dayside magnetosphere, quasi-periodic transient compressions energize radiation belt electrons and ring current ions. Most of these perturbations occur behind the quasi-parallel bow shock, indicating that they are driven by density structures generated by kinetic processes within the foreshock. This presentation compares and contrasts the amplitudes and occurrence patterns of density and dynamic pressure perturbations intrinsic to the solar wind with those generated within the foreshock, specifies how they move across the magnetosphere, examines recent global MHD simulation results for their interaction with the bow shock, magnetosheath, and magnetopause. It then outlines new paths toward quantifying the significance of bursty reconnection to the overall interaction, via new imaging and analysis techniques.

D. G. Sibeck↗
NASA NTRSDate not supplied

Transient Optimization of an Electrified Gas Turbine Engine Using Machine Learning

Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.

Stall Margin↗
NASA NTRS2024

Transient Optimization of an Electrified Gas Turbine Engine Using Machine Learning

Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.

Stall Margin↗