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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

A Learn-To-Fly Approach for Adaptively Tuning Flight Control Systems

A method is presented for adaptively tuning feedback control gains in a ight control sys- tem to achieve desired closed-loop performance. The method combines efficient parameter estimation for identifying closed-loop dynamics models, with online nonlinear optimization for sequentially perturbing and updating control gains to improve performance. Prior in- formation on stability and control derivatives is not needed, nor is any knowledge about the control system architecture. Following convergence, the optimized control gains (with uncertainties), the open-loop dynamics model, and the closed-loop dynamics model are available. The method is demonstrated for tuning a longitudinal stability augmentation system using a realistic nonlinear ight dynamics simulation of the NASA FASER airplane. Convergence was attained using five piloted maneuvers that spanned approximately one minute of ight test time. Although demonstrated for a relatively simple case, the method is general and can be applied to other aircraft, axes, performance metrics, and control systems.

Grauer, Jared A.↗
NASA NTRS2021

A Learn-to-Fly Approach for Adaptively Tuning Flight Control Systems

A method is presented for adaptively tuning feedback control gains in a flight control system to achieve desired closed-loop performance. The method combines efficient aircraft parameter estimation, for identifying closed-loop dynamics models, with online nonlinear optimization, for sequentially perturbing and updating control gains to improve performance. Access to flight measurements and the control gains is required, but no prior information about the aircraft dynamics or the flight control architecture is needed. After the procedure, the optimized control gains (with uncertainties), the open-loop dynamics model, and the closed-loop dynamics model are available. The method is demonstrated for tuning a longitudinal stability augmentation system using a realistic nonlinear flight dynamics simulation of a subscale airplane. Convergence was attained using five maneuvers that spanned approximately one minute of flight test time. Although shown for a relatively simple case, the method is general and can be applied to other aircraft, axes of motion, performance metrics, and control system designs.

Adaptive tuning↗
NASA NTRSDate not supplied

Control and Scaling Approach for the Emulation of Dynamic Subscale Torque Loads

Research and development of electrified aircraft propulsion powertrains is moving toward the use electro-mechanical systems to emulate the loads a system imparts on another. Replacing a prime mover with a model driving an electro-mechanical system capable of emulating loads that regulate the system to produce a desired response is a lower risk, lower cost alternative to using the traditional prime mover for control system verification. This paper outlines a control and scaling approach for emulating scaled dynamic torque loads using electric machine (EM) hardware for electrified aircraft propulsion research and development purposes. The approach, known as the Sliding Mode Impedance Controller with Scaling (SMICS), drives a mechanically coupled two-EM system that provides a scaled hardware representation of an electrified turbomachinery shaft. One EM reflects inertial dynamics and load of the shaft under steady-state and transient operation while the second EM represents a motor/generator connected to the shaft. This closed loop system applies impedance and sliding mode control schemes to match desired dynamics in real-time along with parameter scaling to effectively scale full scale torque inputs, a full-scale desired inertia, and sub-scale speed feedback. The result is a sub-scale hardware implementation of a coupled EM system that is command-able by a model and control system designed for a full-scale electrified aircraft propulsion powertrain. The paper elaborates on the need for closed loop control and scaling as well as impedance and sliding mode control theory, shows a derivation of the controller and scaling, its implementation, and presents a comparison of theoretical and actual simulation results acquired during hardware-in-the-loop testing of a partial turboelectric propulsion concept at the NASA Electric Aircraft Testbed (NEAT).

Santino J Bianco↗
DOE OSTI2022

Technoeconomic Analysis of Changing PV System Layout and Convection Heat Transfer

This work includes analysis of potential economic improvements for PV systems for changing system parameters such as ground coverage ratio that alter the convective cooling consideration on PV modules through a newly proposed convective curve fit. Accounting for the spatial layout of the system in the convection heat transfer calculations allows for more accuracy in convective cooling load and subsequent module temperature calculations. The changing heat transfer considerations can be shown to improve system LCOE along with improved incident irradiance from increased row spacing despite the additional system costs incurred with increased module spacing. State-level analyses show that the impact of decreasing system GCR is greatest for climates with cold average annual ambient temperatures and moderate to high average annual wind speeds. Further waterfall analysis of changing system parameters reveals that the changing heat transfer dynamics have a non-negligible impact on system LCOE when compared to the changes in incident irradiance that serve as the primary driver of annual energy performance changes.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
NASA NTRS1991

Six-Degree-of-Freedom Test Facility

Shuttle to Space station docking has become an important issue in the last few years. Docking sensors have been proposed that will provide high precision measurements required for the fuel efficient rendezvous and docking of space vehicles. These sensors will also be used for satellite servicing and orbital assembly. The performance of the docking sensors must be tested before they are implemented in a space environment. A Six-Degree-of-Freedom (6-DOF) Test Facility has been developed at the Tracking & Communications Section, Johnson Space Center to test the static and dynamic accuracies of docking sensors. A candidate sensor is evaluated by comparing the sensor's static position and velocity measurements to the more accurate 6-DOF system. The 6-DOF Test Facility's hardware is fully integrated. Software has been developed in-house to support system operation. The system has been tested statically and the operational parameters verified. System accuracies remain to be determined. Dynamic testing of the facility is expected to begin shortly. Several companies such as McDonnell Douglas, Autonomous Technologies, and General Dynamics are scheduled to test sensors in the next few months. The 6-DOF facility will be available for use in November 1991. This presentation describes the subcomponents, operation, and capabilities of the 6-DOF Test Facility. Discussions will be held on system accuracies. Additional applications of the 6-DOF system will also be addressed.

Bittel, Michelle A.↗
NASA NTRS2010

Spectral Indices to Monitor Nitrogen-Driven Carbon Uptake in Field Corn

Climate change is heavily impacted by changing vegetation cover and productivity with large scale monitoring of vegetation only possible with remote sensing techniques. The goal of this effort was to evaluate existing reflectance (R) spectroscopic methods for determining vegetation parameters related to photosynthetic function and carbon (C) dynamics in plants. Since nitrogen (N) is a key constituent of photosynthetic pigments and C fixing enzymes, biological C sequestration is regulated in part by N availability. Spectral R information was obtained from field corn grown at four N application rates (0, 70, 140, 280 kg N/ha). A hierarchy of spectral observations were obtained: leaf and canopy with a spectral radiometer; aircraft with the AISA sensor; and satellite with EO-1 Hyperion. A number of spectral R indices were calculated from these hyperspectral observations and compared to geo-located biophysical measures of plant growth and physiological condition. Top performing indices included the R derivative index D730/D705 and the normalized difference of R750 vs. R705 (ND705), both of which differentiated three of the four N fertilization rates at multiple observation levels and yielded high correlations to these carbon parameters: light use efficiency (LUE); C:N ratio; and crop grain yield. These results advocate the use of hyperspectral sensors for remotely monitoring carbon cycle dynamics in managed terrestrial ecosystems.

Corp, Lawrence A.↗
NASA NTRS1982

The problem of split comets in review

Cometary splitting is investigated from the dynamical and physical standpoints. A simple two-parameter model is proposed in which the rate of recession of the fragments is determined by the momentum from outgassing, so that the net differential force is of the same nature as the nongravitational perturbations detected in the motions of unsplit comets; the two parameters of the model are the differential radial acceleration and the time of splitting. It is shown that the model successfully represents the positional observations of nearly all the 21 known split comets. The following candidate triggering mechanisms for cometary splitting are considered: tidal forces, rotation, dust-mantle dumping, and radioactive heating. A model that fits the dynamical data and physical characteristics is presented which suggests that most fragments must be appreciably nonspherical and rapidly precessing.

Sekanina, Z.↗
DOE OSTI2021

Toward Automated Sampling of Polymorph Nucleation and Free Energies with the SGOOP and Metadynamics

Understanding the driving forces behind the nucleation of different polymorphs is of great importance for material sciences and the pharmaceutical industry. This includes understanding the reaction coordinate that governs the nucleation process and correctly calculating the relative free energies of different polymorphs. Here, we demonstrate, for the prototypical case of urea nucleation from the melt, how one can learn such a one-dimensional reaction coordinate as a function of prespecified order parameters and use it to perform efficient biased all-atom molecular dynamics simulations. The reaction coordinate is learnt as a function of the generic thermodynamic and structural order parameters using the “spectral gap optimization of order parameters (SGOOP)” approach [Tiwary, P. and Berne, B. J. Proc. Natl. Acad. Sci. U.S.A. (2016)] and is biased using well-tempered metadynamics simulations. The reaction coordinate gives insights into the role played by different structural and thermodynamics order parameters, and the biased simulations obtain accurate relative free energies for different polymorphs. This includes an accurate prediction of the approximate pressure at which urea undergoes a phase transition and one of the metastable polymorphs becomes the most stable conformation. Here, we believe the ideas demonstrated in this work will facilitate efficient sampling of nucleation in complex, generic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Validation and parameterization of a novel physics-constrained neural dynamics model applied to turbulent fluid flow

We report, in fluid physics, data-driven models to enhance or accelerate time to solution are becoming increasingly popular for many application domains, such as alternatives to turbulence closures, system surrogates, or for new physics discovery. In the context of reduced order models of high-dimensional time-dependent fluid systems, machine learning methods grant the benefit of automated learning from data, but the burden of a model lies on its reduced-order representation of both the fluid state and physical dynamics. In this work, we build a physics-constrained, data-driven reduced order model for Navier–Stokes equations to approximate spatiotemporal fluid dynamics in the canonical case of isotropic turbulence in a triply periodic box. The model design choices mimic numerical and physical constraints by, for example, implicitly enforcing the incompressibility constraint and utilizing continuous neural ordinary differential equations for tracking the evolution of the governing differential equation. We demonstrate this technique on a three-dimensional, moderate Reynolds number turbulent fluid flow. In assessing the statistical quality and characteristics of the machine-learned model through rigorous diagnostic tests, we find that our model is capable of reconstructing the dynamics of the flow over large integral timescales, favoring accuracy at the larger length scales. More significantly, comprehensive diagnostics suggest that physically interpretable model parameters, corresponding to the representations of the fluid state and dynamics, have attributable and quantifiable impact on the quality of the model predictions and computational complexity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1997

Virtual Passive Controller for Robot Systems Using Joint Torque Sensors

This paper presents a control method based on virtual passive dynamic control that will stabilize a robot manipulator using joint torque sensors and a simple joint model. The method does not require joint position or velocity feedback for stabilization. The proposed control method is stable in the sense of Lyaponov. The control method was implemented on several joints of a laboratory robot. The controller showed good stability robustness to system parameter error and to the exclusion of nonlinear dynamic effects on the joints. The controller enhanced position tracking performance and, in the absence of position control, dissipated joint energy.

Aldridge, Hal A.↗
NASA NTRS1986

Parameter estimation and error analysis in environmental modeling and computation

A method for the estimation of parameters and error analysis in the development of nonlinear modeling for environmental impact assessment studies is presented. The modular computer program can interactively fit different nonlinear models to the same set of data, dynamically changing the error structure associated with observed values. Parameter estimation techniques and sequential estimation algorithms employed in parameter identification and model selection are first discussed. Then, least-square parameter estimation procedures are formulated, utilizing differential or integrated equations, and are used to define a model for association of error with experimentally observed data.

Kalmaz, E. E.↗
DOE OSTI2021

Transfer learning of memory kernels for transferable coarse-graining of polymer dynamics

The present work concerns the transferability of coarse-grained (CG) modeling in reproducing the dynamic properties of the reference atomistic systems across a range of parameters. In particular, we focus on implicit-solvent CG modeling of polymer solutions. The CG model is based on the generalized Langevin equation, where the memory kernel plays the critical role in determining the dynamics in all time scales. Thus, we propose methods for transfer learning of memory kernels. The key ingredient of our methods is Gaussian process regression. By integration with the model order reduction via proper orthogonal decomposition and the active learning technique, the transfer learning can be practically efficient and requires minimum training data. Through two example polymer solution systems, we demonstrate the accuracy and efficiency of the proposed transfer learning methods in the construction of transferable memory kernels. The transferability allows for out-of-sample predictions, even in the extrapolated domain of parameters. Built on the transferable memory kernels, the CG models can reproduce the dynamic properties of polymers in all time scales at different thermodynamic conditions (such as temperature and solvent viscosity) and for different systems with varying concentrations and lengths of polymers.

Ma, Zhan↗
NASA NTRS1974

State space representations of distributed fluid line dynamics

The purpose of this paper is to demonstrate the convenience of using a systematic straight forward procedure to obtain meaningful dynamic information for a class of complex distributed parameter fluid line networks. System transients in the time domain are determined by means of state space techniques. Digital computer implementation yields a simple but consistent way of obtaining overall system time solutions. A step-by-step analysis procedure flow chart is shown in Appendix I which illustrates the basic approach for modeling, approximating and selecting digital techniques for simulating the dynamic response of fluid line systems.

Yao, H.↗
NASA NTRS1987

Baseline estimation from simultaneous satellite laser tracking

Simultaneous Range Differences (SRDs) to Lageos are obtained by dividing the observing stations into pairs with quasi-simultaneous observations. For each of those pairs the station with the least number of observations is identified, and at its observing epochs interpolated ranges for the alternate station are generated. The SRD observables are obtained by subtracting the actually observed laser range of the station having the least number of observations from the interpolated ranges of the alternate station. On the basis of these observables semidynamic single baseline solutions were performed. The aim of these solutions is to further develop and implement the SRD method in the real data environment, to assess its accuracy, its advantages and disadvantages as related to the range dynamic mode methods, when the baselines are the only parameters of interest. Baselines, using simultaneous laser range observations to Lageos, were also estimated through the purely geometric method. These baselines formed the standards the standards of comparison in the accuracy assessment of the SRD method when compared to that of the range dynamic mode methods. On the basis of this comparison it was concluded that for baselines of regional extent the SRD method is very effective, efficient, and at least as accurate as the range dynamic mode methods, and that on the basis of a simple orbital modeling and a limited orbit adjustment. The SRD method is insensitive to the inconsistencies affecting the terrestrial reference frame and simultaneous adjustment of the Earth Rotation Parameters (ERPs) is not necessary.

Dedes, George C.↗
NASA NTRS2009

Water Vapor, Temperature, and Ice Particles in Polar Mesosphere as Measured by SABER/TIMED and OSIRIS/Odin Instruments

Although many new details on the properties of mesospheric ice particles that farm Polar Mesospheric Clouds (PMCs) and also cause polar mesospheric summer echoes have been recently revealed, certain aspects of mesospheric ice microphysics and dynamics still remain open. The detailed relation between PMC parameters and properties of their environment, as well as interseasonal and interhemispheric differences and trends in PMC properties that are possibly related to global change, are among those open questions. In this work, mesospheric temperature and water vapor concentration measured by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on board the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite are used to study the properties of PMCs with respect to the surrounding atmosphere. The cloud parameters, namely location, brightness, and altitude, are obtained from the observations made by the Optical Spectrograph and Infrared Imager System (OSIRIS) on the Odin satellite. About a thousand of simultaneous common volume measurements made by SABER and OSIRIS in both hemispheres from 2002 until 2008 are used. The correlation between PMC brightness (and occurrence rate) and temperatures at PMC altitudes and at the mesopause is analysed. The relation between PMC parameters, frost point temperature, and gaseous water vapor content in and below the cloud is also discussed. Interseasonal and interhemispheric differences and trends in the above parameters, as well as in PMC peak altitudes and mesopause altitudes are evaluated.

Feofilov, A. G.↗
DOE OSTI2022

Cross-beam energy transfer in direct-drive ICF. I. Nonlinear and kinetic effects

Results are presented from a series of simulations examining the susceptibility of the cross-beam energy transfer (CBET) instability to nonlinear processes in the context of direct-drive inertial confinement fusion experiments on the OMEGA laser facility. These form the basis for the second paper of this series [A. G. Seaton, L. Yin, R. Follett, B. J. Albright, and A. Le, “Cross-beam energy transfer in direct-drive ICF. II. Theory and simulation of mitigation through increased laser bandwidth,” Phys. Plasmas 29, 042707 (2022)], where we examine the efficacy of increases in laser bandwidth at suppressing CBET. We choose laser and plasma conditions for the simulations that are favorable to CBET and promote nonlinearity. Through a comparison of outputs from the particle-in-cell code vector particle in cell (VPIC) and the linearized fluid code laser-plasma simulation environment (LPSE), a series of nonlinear effects have been identified in the kinetic simulations that include particle trapping, the two-ion wave decay, and ion-acoustic wave self-focusing. These effects produce time-dependent energy transfer, in contrast to the linearized fluid simulations in which a steady state is reached after an initial transient. Ion trapping is shown to allow for increased energy transfer relative to fluid simulations, with the remaining nonlinear processes acting to reduce the energy transfer. Nonlinear dynamics is contrasted for low- and high-intensity beams as well as between speckled and planar beams. For the parameters under consideration, beam profile has a significant effect on nonlinear dynamics, though the greatest sensitivity is to beam intensity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Locating the Source of Forced Oscillations in Transmission Power Grids

A forced oscillation event in power grids refers to a state where malfunctioning or abnormally operating equipment causes persisting periodic disturbances in the system. While power grids are designed to damp most perturbations during standard operations, some of them can excite normal modes of the system and cause significant energy transfers across the system, creating large oscillations thousands of miles away from the source. Localization of the source of such disturbances remains an outstanding challenge due to a limited knowledge of the system parameters outside of the zone of responsibility of system operators. Here, we propose a new method for locating the source of forced oscillations that addresses this challenge by performing a simultaneous dynamic model identification using a principled maximum likelihood approach. We illustrate the validity of the algorithm on a variety of examples where forcing leads to resonance conditions in the system dynamics. Our results establish that an accurate knowledge of system parameters is not required for a successful inference of the source and frequency of a forced oscillation. We anticipate that our method will find a broader application in general dynamical systems that can be well described by their linearized dynamics over short periods of time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2009

Control-Relevant Modeling, Analysis, and Design for Scramjet-Powered Hypersonic Vehicles

Within this paper, control-relevant vehicle design concepts are examined using a widely used 3 DOF (plus flexibility) nonlinear model for the longitudinal dynamics of a generic carrot-shaped scramjet powered hypersonic vehicle. Trade studies associated with vehicle/engine parameters are examined. The impact of parameters on control-relevant static properties (e.g. level-flight trimmable region, trim controls, AOA, thrust margin) and dynamic properties (e.g. instability and right half plane zero associated with flight path angle) are examined. Specific parameters considered include: inlet height, diffuser area ratio, lower forebody compression ramp inclination angle, engine location, center of gravity, and mass. Vehicle optimizations is also examined. Both static and dynamic considerations are addressed. The gap-metric optimized vehicle is obtained to illustrate how this control-centric concept can be used to "reduce" scheduling requirements for the final control system. A classic inner-outer loop control architecture and methodology is used to shed light on how specific vehicle/engine design parameter selections impact control system design. In short, the work represents an important first step toward revealing fundamental tradeoffs and systematically treating control-relevant vehicle design.

Rodriguez, Armando A.↗