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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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NASA NTRS2021

Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data

Domain adaptation techniques have been developed to handle data from multiple sources or domains. Most existing domain adaptation models assume that source and target domains are homogeneous, i.e., they have the same feature space. Nevertheless, many real world applications often deal with data from heterogeneous domains that come from completely different feature spaces. In our remote sensing application, data in source domain (from an active spaceborne Lidar sensor CALIOP onboard CALIPSO satellite) contain 25 attributes, while data in target domain (from a passive spectroradiometer sensor VIIRS onboard Suomi-NPP satellite) contain 20 different attributes. CALIOP has better representation capability and sensitivity to aerosol types and cloud phase, while VIIRS has wide swaths and better spatial coverage but has inherent weakness in differentiating atmospheric objects on different vertical levels. To address this mismatch of features across the domains/sensors, we propose a novel end-to-end deep domain adaptation with domain mapping and correlation alignment (DAMA) to align the heterogeneous source and target domains in active and passive satellite remote sensing data. It can learn domain invariant representation from source and target domains by transferring knowledge across these domains, and achieve additional performance improvement by incorporating weak label information into the model (DAMA-WL). Our experiments on a collocated CALIOP and VIIRS dataset show that DAMA and DAMA-WL can achieve higher classification accuracy in predicting cloud types.

domain adaptation↗

NASA NTRS1975

An application of modern control theory to jet propulsion systems

The control of an airbreathing turbojet engine by an onboard digital computer is studied. The approach taken is to model the turbojet engine as a linear, multivariable system whose parameters vary with engine operating environment. From this model adaptive closed-loop or feedback control laws are designed and applied to the acceleration of the turbojet engine.

Merrill, W. C.↗

NASA NTRS1978

Repeated observation of an uncertain signal

The focus here is on sensory adaptation, or progressively more appropriate attention, as repeated observations yield more information about a signal with an uncertain parameter. The signal was a brief sinusoid; its uncertain parameter was frequency. Detection performance is predicted from data on a signal of known and constant frequency, as a function of the number of frequencies the uncertain signal could assume. A comparison condition presented a signal that varied in a manner not permitting adaptation. Models derived from signal detection theory describe the ideal observation processes for the three signal conditions, and supply quantitative predictions of relative performances. The models are generally supported by the data.

Swets, J. A.↗

NASA NTRS1980

Smoke and dust particles of meteoric origin in the mesosphere and stratosphere

A height profile of ablated mass from meteors is calculated, assuming an incoming mass of 10 to the -16th g/sq cm/s (44 metric tons per day) and the velocity distribution of Southworth and Sekanina, which has a mean of 14.5 km/s. The profile peaks at 84 km. The fluxes of micrometeorites and residual meteoroids are also calculated. The coagulation of the evaporated silicates into 'smoke' particles is then followed by means of a model adapted from a previous study of the stratospheric sulfate layer. Numerous sensitivity tests are made. Features of the results are a sharp cutoff of the particle distribution above 90 km, and a surface area close to 10 to the -9th sq cm/cu cm all the way from 30 to 85 km. Some confirmation is obtained from balloon studies of condensation nuclei, although the various measurements differ greatly. The optical scattering and extinction are shown to be undetectable. Several potential applications are suggested: nucleation of sulfate particles and noctilucent clouds, scavenging of metallic ions and atoms, and perhaps other aeronomical effects. The latter are limited to processes that can be influenced by a collision time of the order of a day.

Hunten, D. M.↗

NASA NTRS1990

Piezoceramic devices and artificial intelligence time varying concepts in smart structures

The problem of development of smart structures and their vibration control by the use of piezoceramic sensors and actuators have been discussed. In particular, these structures are assumed to have time varying model form and parameters. The model form may change significantly and suddenly. Combined identification of the model from parameters of these structures and model adaptive control of these structures are discussed in this paper.

Hanagud, S.↗

NASA NTRS1992

Computational methods in the prediction of advanced subsonic and supersonic propeller induced noise: ASSPIN users' manual

This document describes the computational aspects of propeller noise prediction in the time domain and the use of high speed propeller noise prediction program ASSPIN (Advanced Subsonic and Supersonic Propeller Induced Noise). These formulations are valid in both the near and far fields. Two formulations are utilized by ASSPIN: (1) one is used for subsonic portions of the propeller blade; and (2) the second is used for transonic and supersonic regions on the blade. Switching between the two formulations is done automatically. ASSPIN incorporates advanced blade geometry and surface pressure modelling, adaptive observer time grid strategies, and contains enhanced numerical algorithms that result in reduced computational time. In addition, the ability to treat the nonaxial inflow case has been included.

Dunn, M. H.↗

NASA NTRS1999

Meteorology of the Southern Global Plume: African and South American Fires Pollute the South Pacific

An immense global plume of CO meanders widely around the world in the Southern Hemisphere. It arises over Southern America and Africa and flows eastward. The first emissions are in tropical Brazil, and the plume circulates around the world to South America again. The plume was largely unexpected until there were aircraft studies made in NASA's Pacific Exploratory Mission - Tropics (Part A). This paper describes the meteorology of the Global Plume, as our simulation, with a synoptic model adapted to global transport, reveals it with a tracer-CO simulation. The observations and their simulation require a particular set of conditions of pollutant accumulation, cumulonimbus venting with required strengths at a narrow range of altitude. Additionally, a particular subtropical conduction region, over the Indian Ocean, Australia, and the westeRNmost South Pacific, relatively free of storms, appears to be a key part of the mechanism. These conclusions are the results of a synoptic reconstruction of the PEMT-A period, September- October, 1996.

Guo, Z.↗

NASA NTRS2005

Application of a Constant Gain Extended Kalman Filter for In-Flight Estimation of Aircraft Engine Performance Parameters

An approach based on the Constant Gain Extended Kalman Filter (CGEKF) technique is investigated for the in-flight estimation of non-measurable performance parameters of aircraft engines. Performance parameters, such as thrust and stall margins, provide crucial information for operating an aircraft engine in a safe and efficient manner, but they cannot be directly measured during flight. A technique to accurately estimate these parameters is, therefore, essential for further enhancement of engine operation. In this paper, a CGEKF is developed by combining an on-board engine model and a single Kalman gain matrix. In order to make the on-board engine model adaptive to the real engine s performance variations due to degradation or anomalies, the CGEKF is designed with the ability to adjust its performance through the adjustment of artificial parameters called tuning parameters. With this design approach, the CGEKF can maintain accurate estimation performance when it is applied to aircraft engines at offnominal conditions. The performance of the CGEKF is evaluated in a simulation environment using numerous component degradation and fault scenarios at multiple operating conditions.

Kobayashi, Takahisa↗

NASA NTRS2007

Quaternion Averaging

Many applications require an algorithm that averages quaternions in an optimal manner. For example, when combining the quaternion outputs of multiple star trackers having this output capability, it is desirable to properly average the quaternions without recomputing the attitude from the the raw star tracker data. Other applications requiring some sort of optimal quaternion averaging include particle filtering and multiple-model adaptive estimation, where weighted quaternions are used to determine the quaternion estimate. For spacecraft attitude estimation applications, derives an optimal averaging scheme to compute the average of a set of weighted attitude matrices using the singular value decomposition method. Focusing on a 4-dimensional quaternion Gaussian distribution on the unit hypersphere, provides an approach to computing the average quaternion by minimizing a quaternion cost function that is equivalent to the attitude matrix cost function Motivated by and extending its results, this Note derives an algorithm that deterniines an optimal average quaternion from a set of scalar- or matrix-weighted quaternions. Rirthermore, a sufficient condition for the uniqueness of the average quaternion, and the equivalence of the mininiization problem, stated herein, to maximum likelihood estimation, are shown.

Markley, F. Landis↗

NASA NTRS2007

Reconfigurable Control Design with Neural Network Augmentation for a Modified F-15 Aircraft

The viewgraphs present background information about reconfiguration control design, design methods used for paper, control failure survivability results, and results and time histories of tests. Topics examined include control reconfiguration, general information about adaptive controllers, model reference adaptive control (MRAC), the utility of neural networks, radial basis functions (RBF) neural network outputs, neurons, and results of investigations of failures.

Burken, John J.↗

NASA NTRS2010

Parametric Geometry, Structured Grid Generation, and Initial Design Study for REST-Class Hypersonic Inlets

Computational design and analysis of three-dimensional hypersonic inlets with shape transition has been a significant challenge due to the complex geometry and grid required for three-dimensional viscous flow calculations. Currently, the design process utilizes an inviscid design tool to produce initial inlet shapes by streamline tracing through an axisymmetric compression field. However, the shape is defined by a large number of points rather than a continuous surface and lacks important features such as blunt leading edges. Therefore, a design system has been developed to parametrically construct true CAD geometry and link the topology of a structured grid to the geometry. The Adaptive Modeling Language (AML) constitutes the underlying framework that is used to build the geometry and grid topology. Parameterization of the CAD geometry allows the inlet shapes produced by the inviscid design tool to be generated, but also allows a great deal of flexibility to modify the shape to account for three-dimensional viscous effects. By linking the grid topology to the parametric geometry, the GridPro grid generation software can be used efficiently to produce a smooth hexahedral multiblock grid. To demonstrate the new capability, a matrix of inlets were designed by varying four geometry parameters in the inviscid design tool. The goals of the initial design study were to explore inviscid design tool geometry variations with a three-dimensional analysis approach, demonstrate a solution rate which would enable the use of high-fidelity viscous three-dimensional CFD in future design efforts, process the results for important performance parameters, and perform a sample optimization.

Ferlemann, Paul G.↗

NASA NTRS2012

Integrated Design Engineering Analysis (IDEA) Environment Automated Generation of Structured CFD Grids using Topology Methods

This report documents the work performed from March 2010 to March 2012. The Integrated Design and Engineering Analysis (IDEA) environment is a collaborative environment based on an object-oriented, multidisciplinary, distributed framework using the Adaptive Modeling Language (AML) as a framework and supporting the configuration design and parametric CFD grid generation. This report will focus on describing the work in the area of parametric CFD grid generation using novel concepts for defining the interaction between the mesh topology and the geometry in such a way as to separate the mesh topology from the geometric topology while maintaining the link between the mesh topology and the actual geometry.

Kamhawi, Hilmi N.↗

NASA NTRS2011

Integrated Design Engineering Analysis (IDEA) Environment - Aerodynamics, Aerothermodynamics, and Thermal Protection System Integration Module

This report documents the work performed during from March 2010 October 2011. The Integrated Design and Engineering Analysis (IDEA) environment is a collaborative environment based on an object-oriented, multidisciplinary, distributed environment using the Adaptive Modeling Language (AML) as the underlying framework. This report will focus on describing the work done in the area of extending the aerodynamics, and aerothermodynamics module using S/HABP, CBAERO, PREMIN and LANMIN. It will also detail the work done integrating EXITS as the TPS sizing tool.

Kamhawi, Hilmi N.↗

NASA NTRS2013

Integrated Design and Engineering Analysis (IDEA) Environment - Propulsion Related Module Development and Vehicle Integration

This report documents the work performed during the period from May 2011 - October 2012 on the Integrated Design and Engineering Analysis (IDEA) environment. IDEA is a collaborative environment based on an object-oriented, multidisciplinary, distributed framework using the Adaptive Modeling Language (AML). This report will focus on describing the work done in the areas of: (1) Integrating propulsion data (turbines, rockets, and scramjets) in the system, and using the data to perform trajectory analysis; (2) Developing a parametric packaging strategy for a hypersonic air breathing vehicles allowing for tank resizing when multiple fuels and/or oxidizer are part of the configuration; and (3) Vehicle scaling and closure strategies.

Kamhawi, Hilmi N.↗

NASA NTRS2016

Dynamic Filtering Improves Attentional State Prediction with fNIRS

Brain activity can predict a person's level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise - thereby increasing such state prediction accuracy - remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% +/- 6% versus 72% +/- 15%).

Harrivel, Angela R.↗

NASA NTRS2014

M-MRAC With Normalization

This paper presents a normalization based modified reference model adaptive control method for multi-input multi-output (MIMO) uncertain systems in the presence of bounded external disturbances. It has been shown that desired tracking performance can be achieved for the system's output and input signals with the proper choice of design parameters. The resulting adaptive control signal satisfies a second order linear time invariant (LTI) system, which is the effect of the normalization term in the adaptive laws. This LTI system provides the guideline for the design parameter selection. The theoretical findings are confirmed via a simulation example.

Stepanyan, Vahram↗

NASA NTRS2018

Performance of Cassini Reaction Wheel Friction Compensation Scheme During Spin Rate Zero-Crossing and Drag Spikes

Cassini uses reaction wheels to achieve the spacecraft pointing stability that is needed during imaging operations of several science instruments. The Cassini flight software makes inflight estimates of reaction wheel bearing drag torque and the reaction wheel controller uses these estimates to achieve a high level of spacecraft pointing stability. However, the Cassini drag torque estimator was designed to accurately track the bearing drag torque only in the steady state. When the physical drag torque changes abruptly (for example, during a reaction wheel spin rate reversal or when wheel bearings experienced drag spikes), the drag estimator will not be able to track the physical drag closely. This will lead to a degradation in the spacecraft pointing stability performance. For Cassini, this was not a problem because of the significant performance margin in pointing stability. However, for missions that have very challenging pointing stability requirements and that must perform well in the presence of frequent wheel rate reversals, alternative drag-compensating control schemes must be considered. To this end, alternative drag torque compensating control schemes (such as the adaptive model reference control scheme) are briefly reviewed in this paper. Selected design features used in these friction compensation schemes may be incorporated in reaction wheel controller design to improve the robustness of spacecraft pointing stability performance with regard to a wide range of reaction wheel drag torque anomalous behavior.

Lee, Allan Y↗

NASA NTRSDate not supplied

Developing and Testing a Physics Guided Machine Learning NeuralNetwork to Predict Tonal Noise Emitted by a Propeller

Artificial neural networks offer a highly nonlinear and adaptive model for predicting complex interactions between input-output parameters. However, these networks require large datasets which often exceed practical considerations in modeling experimental results. To alleviate the dataset size requirement, a method known as physics guided machine learning has been applied to construct several neural networks for predicting propeller tonal noise in the time domain over a broad range of flight conditions. Three space-filling designs, namely, Latin-Hypercube, Sphere-Packing, and Grid-Space, were used to distribute points throughout the input parameter space encompassing nondimensional flight conditions and observer geometry. Each neural network’s performance was validated by conditions outside of the training set and compared to the Propeller Analysis System tool from the NASA Aircraft Noise Prediction Program. Compared to the Grid-Space input design, the Latin-Hypercube and the Sphere-Packing designs provided a better representation of the domain for training. Regarding the network archetype, a fully connected perceptron was found to outperform the partially connected perceptron in their ability to predict tonal noise for small datasets. The black-box nature of these neural networks was also explored to understand how the networks constructed the waveform and understand why some network designs produce better models.

Propeller noise↗