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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 199 records · Page 11

All sources NASA NTRS DOE OSTI

NASA NTRS1992

Stratified Charge Rotary Engine Critical Technology Enablement, Volume 1

This report summarizes results of a critical technology enablement effort with the stratified charge rotary engine (SCRE) focusing on a power section of 0.67 liters (40 cu. in.) per rotor in single and two rotor versions. The work is a continuation of prior NASA Contracts NAS3-23056 and NAS3-24628. Technical objectives are multi-fuel capability, including civil and military jet fuel and DF-2, fuel efficiency of 0.355 Lbs/BHP-Hr. at best cruise condition above 50 percent power, altitude capability of up to 10Km (33,000 ft.) cruise, 2000 hour TBO and reduced coolant heat rejection. Critical technologies for SCRE's that have the potential for competitive performance and cost in a representative light-aircraft environment were examined. Objectives were: the development and utilization of advanced analytical tools, i.e. higher speed and enhanced three dimensional combustion modeling; identification of critical technologies; development of improved instrumentation, and to isolate and quantitatively identify the contribution to performance and efficiency of critical components or subsystems.

Irion, C. E.↗

NASA NTRS1992

Stratified charge rotary engine critical technology enablement. Volume 2: Appendixes

This second volume of appendixes is a companion to Volume 1 of this report which summarizes results of a critical technology enablement effort with the stratified charge rotary engine (SCRE) focusing on a power section of 0.67 liters (40 cu. in.) per rotor in single and two rotor versions. The work is a continuation of prior NASA Contracts NAS3-23056 and NAS3-24628. Technical objectives are multi-fuel capability, including civil and military jet fuel and DF-2, fuel efficiency of 0.355 Lbs/BHP-Hr. at best cruise condition above 50 percent power, altitude capability of up to 10Km (33,000 ft.) cruise, 2000 hour TBO and reduced coolant heat rejection. Critical technologies for SCRE's that have the potential for competitive performance and cost in a representative light-aircraft environment were examined. Objectives were: the development and utilization of advanced analytical tools, i.e. higher speed and enhanced three dimensional combustion modeling; identification of critical technologies; development of improved instrumentation; and to isolate and quantitatively identify the contribution to performance and efficiency of critical components or subsystems. A family of four-stage third-order explicit Runge-Kutta schemes is derived that required only two locations and has desirable stability characteristics. Error control is achieved by embedding a second-order scheme within the four-stage procedure. Certain schemes are identified that are as efficient and accurate as conventional embedded schemes of comparable order and require fewer storage locations.

Irion, C. E.↗

NASA NTRS2015

Effects of False Tilt Cues on the Training of Manual Roll Control Skills

This paper describes a transfer-of-training study performed in the NASA Ames Vertica lMotion Simulator. The purpose of the study was to investigate the effect of false tilt cues on training and transfer of training of manual roll control skills. Of specific interest were the skills needed to control unstable roll dynamics of a mid-size transport aircraft close to the stall point. Nineteen general aviation pilots trained on a roll control task with one of three motion conditions: no motion, roll motion only, or reduced coordinated roll motion. All pilots transferred to full coordinated roll motion in the transfer session. A novel multimodal pilot model identification technique was successfully applied to characterize how pilots' use of visual and motion cues changed over the course of training and after transfer. Pilots who trained with uncoordinated roll motion had significantly higher performance during training and after transfer, even though they experienced the false tilt cues. Furthermore, pilot control behavior significantly changed during the two sessions, as indicated by increasing visual and motion gains, and decreasing lead time constants. Pilots training without motion showed higher learning rates after transfer to the full coordinated roll motion case.

simulators↗

NASA NTRS2019

Unsteady Model Estimation for Generic T-Tail Transport Aircraft Using Computational Data

Models including nonlinear and unsteady behaviors are developed for the longitudinal axis of the NASA Generic T-Tail Aircraft over a large range of angle of attack. These models are based on computational simulations of forced-oscillation tests in a wind tunnel. This work continues a recent study and an ongoing effort by NASA to improve aircraft simulations for pilot training in loss-of-control and stalled conditions. The objective of this work is to develop appropriate aerodynamic models that provide representative responses in simulation for a given class of aircraft. In the stall region, nonlinear unsteady responses are often present and may require an extended aerodynamic model compared to that used in the conventional flight envelope. In this study, two objectives are addressed. The first is to obtain representative models for the NASA Generic T-Tail aircraft over a wide range of angle of attack and the second is to continue development of a specialized CFD test technique that uses Schroeder sweeps to create information rich responses for unsteady aerodynamic model identification.

Murphy, Patrick C.↗

NASA NTRSDate not supplied

Creating Formal Characterizations of Routine Contingency Management in Commercial Aviation

The identification, modelling, and analysis of root causes of accidents and incidents dominate conventional safety management approaches. However, the effect of humans’ safety-producing behavior on the overall resilience of the system is often neglected. Additionally, emerging aviation markets are giving rise to concepts of operation, such as urban air mobility and optionally piloted air cargo operations, that are leading to a shift in locus of control between humans and automation. Without an understanding of the human contribution to safety, it is difficult to assess the effects of these novel role allocations on overall system safety. In this work, safety-producing behaviors are identified and abstracted into resilient performance strategies. Production rules that encapsulate these strategies are then generated and classified in the Soar cognitive architecture. The strategies are then applied to a remotely-operated air cargo example to demonstrate how safe learning is facilitated. The learned rules and strategies are then formally verified.

Safety Critical Systems↗

DOE OSTI2016

Application of periodic perturbations to a RELAP5 hydraulic simulation to determine frequency response

Time series analysis requires a collection of data taken sequentially in time to apply techniques for identification, modeling, prediction or control purposes. Some systems operating at steady state are perturbed with white noise to extract system information using autoregressive models or spectral analysis, and then the dynamic response is used to assess system properties. If it is not possible to perturb the physical system, a mathematical model can be used to work with and study the perturbation effect. In this work, the system object of perturbation study is a RELAP5 hydraulic model, and since the excitation with a white noise sequence is not readily implementable, an alternative is proposed to apply a series of periodic steps in a square wave pattern. With this periodic excitation, the output of a RELAP5 model for a hydraulic piping system can be analyzed with frequency domain tools. The piping systems can be found in the balance of plant of a steam power plant, and the aim of this work is to explore the capability of RELAP5 to determine system frequency characteristics linked to mechanical vibration in operating lines of a power plant. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Investigation and Mitigation of a Prominent Off-Axis Stray Light Path in Rubin Observatory Commissioning

The "scratched tape" stray light feature is the most prominent and prevalent stray light artifact identified during the commissioning of the Vera C. Rubin Observatory. The scratched tape feature originates when light from large off-axis angles (~20 deg) passes between the mid-level and center-section light baffles, reflects off the primary mirror, and illuminates the LSST Camera focal plane. This scenario represented an unobstructed stray light path to the sky during Rubin commissioning due to delays in the integration of the dome slit light-wind screen. This document describes the identification, modeling, characterization, and mitigation of the scratched tape stray light artifact.

Drlica-Wagner, Alex [Fermilab; Chicago U., Astron.↗

NASA NTRS1993

Fusing modeling techniques to support domain analysis for reuse opportunities identification

Functional modeling techniques or object-oriented graphical representations, which are more useful to someone trying to understand the general design or high level requirements of a system? For a recent domain analysis effort, the answer was a fusion of popular modeling techniques of both types. By using both functional and object-oriented techniques, the analysts involved were able to lean on their experience in function oriented software development, while taking advantage of the descriptive power available in object oriented models. In addition, a base of familiar modeling methods permitted the group of mostly new domain analysts to learn the details of the domain analysis process while producing a quality product. This paper describes the background of this project and then provides a high level definition of domain analysis. The majority of this paper focuses on the modeling method developed and utilized during this analysis effort.

Hall, Susan Main↗

NASA NTRS1967

Learning models for adaptive system identification, part A Final report

Learning models for identification, adaptation, and sensitivity of optimal control systems

Sherman, J. W.↗

NASA NTRS1993

High-resolution measurements, line identification, and spectral modeling of K-alpha transitions in Fe XVIII-Fe XXV

A detailed analysis of the iron K-alpha emission spectrum covering the wavelength region from 1.840 to 1.940 A is presented. Measurements are made with a high-resolution Bragg crystal spectrometer on the Princeton Large Torus (PLT) tokamak for plasma conditions which closely resemble those of solar flares. A total of 40 features are identified, consisting of either single or multiple lines from eight charge states in iron, Fe XVIII - Fe XXV, and their wavelengths are determined with an accuracy of 0.1-0.4 mA. Many of these features are identified for the first time. In the interpretation of our observations we rely on model calculations that determine the ionic species abundances from electron density and temperature profiles measured independently with nonspectroscopic techniques and that incorporate theoretical collisional excitation and dielectronic recombination rates resulting in the excitation of the 1s2sr2ps configurations. The model calculations also include the effect of diffusive ion transport. Good overall agreement between the model calculations and the observations is obtained, which gives us confidence in our line identifications and spectral modeling capabilities. The results are compared with earlier analyses of the K-alpha emission from the Sun.

Beiersdorfer, P.↗

NASA NTRS1974

Computer experiments in preparation of system identification from transient rotor model tests, part 2

System identification methods which can extract model rotor paramenters with reasonable accuracy from noise polluted blade flapping transient measurements were developed. Usually parameter identification requires data on the state variables, that is on deflections and on rate of deflections. The small size of rotor models makes it, however, difficult to measure more than the blade flapping deflections. For the computer experiments it was, therefore, assumed that only noisy deflection measurements are available. Parameter identifications were performed for one and two unknown parameters. Both rotating coordinates and multiblade coordinates were used. It was found that data processing with a digital filter allowed by numerical differentiation a sufficiently accurate determination of the rates of deflection and of the accelerations to obtain reasonable parameter estimates with a simple linear estimator.

Hohenemser, K. H.↗

DOE OSTI2018

Overhead longwave infrared hyperspectral material identification using radiometric models

Material detection algorithms used in hyperspectral data processing are computationally efficient but can produce relatively high numbers of false positives. Material identification performed as a secondary processing step on detected pixels can help separate true and false positives. This paper presents a material identification processing chain for longwave infrared hyperspectral data of solid materials collected from airborne platforms. The algorithms utilize unwhitened radiance data and an iterative algorithm that determines the temperature, humidity, and ozone of the atmospheric profile. Pixel unmixing is done using constrained linear regression and Bayesian Information Criteria for model selection. The resulting product includes an optimal atmospheric profile and full radiance material model that includes material temperature, abundance values, and several fit statistics. A logistic regression method utilizing all model parameters to improve identification is also presented. This paper details the processing chain and provides justification for the algorithms used. Several examples are provided using modeled data at different noise levels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗

DOE OSTI2013

Modeling, Real-Time Estimation, and Identification of UWB Indoor Wireless Channels

Stochastic differential equations (SDEs) are used to model ultrawideband (UWB) indoor wireless channels. We show that the impulse responses for time-varying indoor wireless channels can be approximated in a mean-square sense as close as desired by impulse responses that can be realized by SDEs. The state variables represent the inphase and quadrature components of the UWB channel. The expected maximization and extended Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Both resolvable and nonresolvable multipath received signals are considered and represented as small-scaled Nakagami fading. The proposed models together with the estimation algorithm are tested using UWB indoor measurement data demonstrating the method’s viability and the results are presented.

Olama, Mohammed M.↗

NASA NTRS1988

On the problem of modeling for parameter identification in distributed structures

Structures are often characterized by parameters, such as mass and stiffness, that are spatially distributed. Parameter identification of distributed structures is subject to many of the difficulties involved in the modeling problem, and the choice of the model can greatly affect the results of the parameter identification process. Analogously to control spillover in the control of distributed-parameter systems, identification spillover is shown to exist as well and its effect is to degrade the parameter estimates. Moreover, as in modeling by the Rayleigh-Ritz method, it is shown that, for a Rayleigh-Ritz type identification algorithm, an inclusion principle exists in the identification of distributed-parameter systems as well, so that the identified natural frequencies approach the actual natural frequencies monotonically from above.

Norris, Mark A.↗

NASA NTRS1989

On the problem of modeling for parameter identification in distributed structures

Norris, Mark A.↗

NASA NTRS1982

Parametric identification of human operator models

The accurate and efficient identification of the human operator is still a need in human factors engineering especially concerning multivariable control. Control theoretic identification methods need to be tested with human operator models under realistic boundary conditons. The requirements and criteria for the use of parametric methods, selected models as well as the Maximum Likelihood Method and the Extended Kalman Filter are displayed. The experiments and results are comparatively discussed from the point of practical engineering.

Ninz, N. R.↗

NASA NTRS1987

Modeling XV-15 tilt-rotor aircraft dynamics by frequency and time-domain identification techniques

Models of the open-loop hover dynamics of the XV-15 Tilt-Rotor Aircraft are extracted from flight data using two approaches: frequency domain and time-domain identification. Both approaches are reviewed and the identification results are presented and compared in detail. The extracted models are compared favorably, with the differences associated mostly with the inherent weighing of each technique. Step responses are used to show that the predictive capability of the models from both techniques is excellent. Based on the results of this study, the relative strengths and weaknesses of the frequency and time-domain techniques are summarized and a proposal for a coordinated parameter identification approach is presented.

Tischler, Mark B.↗