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At least 397 records · Page 22

Applicability of a Framework for Estimating Performance and Associated Uncertainty for Modified Aircraft Configurations

As improvements are made to the accuracy and reliability of modeling and simulation techniques, certification by analysis becomes a more attractive alternative compared to traditional aircraft flight testing. Certification by analysis is especially cost-effective when one considers modifications to a previously certified aircraft. However, it is important that the models and methods used are applicable and accurate throughout the intended use domain. A framework for estimating the performance and associated uncertainty was introduced in an earlier paper. The factors and limitations of this framework for estimating the performance and associated model form uncertainty are explored to determine the range of applicability of the framework, particularly with respect to model form, process and sensor noise, and quality of available flight test data. This paper focuses on the general limitations and applicability of the framework and not the applicability of the individual methods to a range of modified configurations, which requires a large number of modified configurations and is an area for future work. The effects of these factors on the performance and uncertainty results are demonstrated using NASA’s Generic Transport Model aircraft.

uncertainty quantification↗

Uncertainty Quantification using Deep Ensembles for Decision Making in Cyber-Physical-Human Systems

In this paper and its companion, Differential Equation Approximation Using Gradient-Boosted Quantile Regression, Robison et al., we examine an approach to quantifying model uncertainty with the aim of increasing the trustworthiness of computational models in human-machine interactions. In Differential Equation Approximation Using Gradient-Boosted Quantile Regression, we focus on gradient-boosted decision trees, while in this one, we give more details about deep ensembles. Uncertainty quantification is crucial for building trustworthy autonomous decision-making agents in human-machine teams. There are two types of uncertainties: aleatoric and epistemic. The former is related to the inherent stochasticity (noise) of the process, whereas the latter is associated with the lack of knowledge or representation capability of models, such as neural networks. By lack of knowledge, we mean the model’s inability to accurately predict outputs for all possible inputs. The aleatory uncertainty can be estimated fairly easily with, for example, filters, whereas epistemic uncertainty is challenging to compute. This paper uses deep ensembles to quantify both aleatory and epistemic uncertainty. It can act as an uncertainty-aware surrogate transition model for decision-making frameworks. "Uncertainty-aware" means that the surrogate transition model should make predictions along with confidence in those predictions. In the context of decision-making, the transition models are ordinary differential equations (ODEs). Since ODEs can be simulated to make one-step or multi-step predictions, a good surrogate model for them should perform reasonably well in both modes. In a multi-step approach, the trajectory sampling method TS∞ was used to propagate uncertainty over multiple steps. The cartpole dynamical system was selected to demonstrate the ability of deep ensembles as good surrogate transition models for decision-making frameworks. The deep ensembles modeled the dynamics of cartpole ODEs and made uncertainty-aware predictions in single-step and multi-step transition modes.

CPH systems↗

Noise equivalent circuit of a semiconductor laser diode

A small-signal model of a semiconductor laser is extended to include the effects of intrinsic noise by adding current and voltage noise sources. The current noise source represents the shot noise of carrier recombination, while the voltage noise source represents the random process of simulated emission. The usefulness of the noise equivalent circuit is demonstrated by calculating the modulation and noise characteristics of a current-driven diode as a function of bias current and frequency.

Harder, C.↗

In-flight estimation of gyro noise on the Upper Atmosphere Research Satellite (UARS) and Extreme Ultraviolet Explorer (EUVE) missions

This paper characterizes the low-frequency noise response of the Teledyne dry rotor inertial reference unit (DRIRU) gyroscopes on the Upper Atmosphere Research Satellite (UARS) and the Extreme Ultraviolet Explorer (EUVE). The accuracy of spacecraft attitude estimation algorithms that use gyro data for propagating the spacecraft attitude is sensitive to gyro noise. EUVE gyro data were processed to validate a single-axis gyro noise model, which is used onboard various spacecraft. The paper addresses the potential impact of temperature effects on the gyro noise model and the overall impact on attitude determination accuracy. The power spectral density (PSD) of the gyro noise is estimated from UARS in-flight data by Fast Fourier Transform (FFT). The role of actuator dynamics on the PSD function is also discussed.

Lee, M.↗

Auralization Architectures for NASA?s Next Generation Aircraft Noise Prediction Program

Aircraft community noise is a significant concern due to continued growth in air traffic, increasingly stringent environmental goals, and operational limitations imposed by airport authorities. The assessment of human response to noise from future aircraft can only be afforded through laboratory testing using simulated flyover noise. Recent work by the authors demonstrated the ability to auralize predicted flyover noise for a state-of-the-art reference aircraft and a future hybrid wing body aircraft concept. This auralization used source noise predictions from NASA's Aircraft NOise Prediction Program (ANOPP) as input. The results from this process demonstrated that auralization based upon system noise predictions is consistent with, and complementary to, system noise predictions alone. To further develop and validate the auralization process, improvements to the interfaces between the synthesis capability and the system noise tools are required. This paper describes the key elements required for accurate noise synthesis and introduces auralization architectures for use with the next-generation ANOPP (ANOPP2). The architectures are built around a new auralization library and its associated Application Programming Interface (API) that utilize ANOPP2 APIs to access data required for auralization. The architectures are designed to make the process of auralizing flyover noise a common element of system noise prediction.

Rizzi, Stephen A.↗

Signal-to-noise ratios in IUE SWP-LO spectra of chromospheric emission-line sources

The short-wavelength-prime (SWP) detector of the International Ultraviolet Explorer should operate near the photon-counting limit, but the noise levels in flat-field images are several times higher. The exaggerated noise can be traced to the incomplete removal of the pixel-to-pixel granularity of the television frames by the prevailing spectral image processing system. An empirical noise model for the current-epoch photometric linearization strategy and one for a hypothetical processing system that achieves complete flat fielding of the raw images are derived. A formula is then proposed to predict the signal-to-noise ratio in the measured flux of an emission line (possibly superimposed on a smooth continuum) in an IUE low-dispersion (5 A resolution) far-ultraviolet (1150 A-1950 A) spectrum as recorded with the SWP camera. For illustration, the formula is specialized to the important C IV 1549 A feature of F-K stars. The S/N relation permits one to determine sensitivity limits, upper limits in faint exposures, and optimum exposure times.

Ayres, Thomas R.↗

New approach to the design of Schottky barrier diodes for THz mixers

Near-ideal GaAs Schottky barrier diodes especially designed for mixing applications in the THz frequency range are presented. A diode fabrication process for submicron diodes with near-ideal electrical and noise characteristics is described. This process is based on the electrolytic pulse etching of GaAs in combination with an in-situ platinum plating for the formation of the Schottky contacts. Schottky barrier diodes with a diameter of 1 micron fabricated by the process have already shown excellent results in a 650 GHz waveguide mixer at room temperature. A conversion loss of 7.5 dB and a mixer noise temperature of less than 2000 K have been obtained at an intermediate frequency of 4 GHz. The optimization of the diode structure and the technology was possible due to the development of a generalized Schottky barrier diode model which is valid also at high current densities. The common diode design and optimization is discussed on the basis of the classical theory. However, the conventional fomulas are valid only in a limited forward bias range corresponding to currents much smaller than the operating currents under submillimeter mixing conditions. The generalized new model takes into account not only the phenomena occurring at the junction such as current dependent recombination and drift/diffusion velocities, but also mobility and electron temperature variations in the undepleted epi-layer. Calculated diode I/V and noise characteristics are in excellent agreement with the measured values. Thus, the model offers the possibility of optimizing the diode structure and predicting the diode performance under mixing conditions at THz frequencies.

Jelenski, A.↗

Fluid dynamic aspects of jet noise generation

The propagation of sound waves inside a jet (single or multiple) was studied with particular attention to refraction of ray trajectories and distortion of wave profile due to nonlinear effects. An experimental method is used in studying this phenomenon which consists of injecting from outside the jet, at one or various points near the mixing zone, a set of pressure signals, and detecting them with one or more microphones placed inside the jet. The signals are detected in the presence of the background noise of the jet itself. Signal processing and instrumentation are discussed along with noise detection.

Source record↗

Improved Broadband Liner Optimization Applied to the Advanced Noise Control Fan

The broadband component of fan noise has grown in relevance with the utilization of increased bypass ratio and advanced fan designs. Thus, while the attenuation of fan tones remains paramount, the ability to simultaneously reduce broadband fan noise levels has become more desirable. This paper describes improvements to a previously established broadband acoustic liner optimization process using the Advanced Noise Control Fan rig as a demonstrator. Specifically, in-duct attenuation predictions with a statistical source model are used to obtain optimum impedance spectra over the conditions of interest. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners aimed at producing impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increased weighting to specific frequencies and/or operating conditions. Constant-depth, double-degree of freedom and variable-depth, multi-degree of freedom designs are carried through design, fabrication, and testing to validate the efficacy of the design process. Results illustrate the value of the design process in concurrently evaluating the relative costs/benefits of these liner designs. This study also provides an application for demonstrating the integrated use of duct acoustic propagation/radiation and liner modeling tools in the design and evaluation of novel broadband liner concepts for complex engine configurations.

Nark, Douglas M.↗

AAFE man-made noise experiment project. Volume 2: Project and experiment discussions

An experiment for the acquisition and processing of man-made noise interference data on earth orbital altitudes is discussed. The objectives of the project are to confirm the results of analytical studies concerning radio frequency man-made noise in space. It is stated that the measurements of the amounts and types of noise in frequency bands of interest could allow the allocation and utilization of frequencies to be optimized and would also contribute to the engineering objective of optimizing flight receiving systems. A second objective of the project was to design and fabricate a noise measuring receiver which would demonstrate the feasibility of the experiment design under the project. The procedures for acquiring and processing the electromagnetic radiation data are discussed.

Source record↗

Reducing Centroid Error Through Model-Based Noise Reduction

A method of processing the digitized output of a charge-coupled device (CCD) image detector has been devised to enable reduction of the error in computed centroid of the image of a point source of light. The method involves model-based estimation of, and correction for, the contributions of bias and noise to the image data. The method could be used to advantage in any of a variety of applications in which there are requirements for measuring precise locations of, and/or precisely aiming optical instruments toward, point light sources. In the present method, prior to normal operations of the CCD, one measures the point-spread function (PSF) of the telescope or other optical system used to project images on the CCD. The PSF is used to construct a database of spot models representing the nominal CCD pixel outputs for a point light source projected onto the CCD at various positions incremented by small fractions of a pixel.

Lee, Shinhak↗

An analytical method for designing low noise helicopter transmissions

The development and experimental validation of a method for analytically modeling the noise mechanism in the helicopter geared power transmission systems is described. This method can be used within the design process to predict interior noise levels and to investigate the noise reducing potential of alternative transmission design details. Examples are discussed.

Bossler, R. B., Jr.↗

Modeling of Broadband Liners Applied to the Advanced Noise Control Fan

The broadband component of fan noise has grown in relevance with an increase in bypass ratio and incorporation of advanced fan designs. Therefore, while the attenuation of fan tones remains a major factor in engine nacelle acoustic liner design, the simultaneous reduction of broadband fan noise levels has received increased interest. As such, a previous investigation focused on improvements to an established broadband acoustic liner optimization process using the Advanced Noise Control Fan (ANCF) rig as a demonstrator. Constant-depth, double-degree of freedom and variable-depth, multi-degree of freedom liner designs were carried through design, fabrication, and testing. This paper addresses a number of areas for further research identified in the initial assessment of the ANCF study. Specifically, incident source specification and uncertainty in some aspects of the predicted liner impedances are addressed. This information is incorporated in updated predictions of the liner performance and comparisons with measurement are greatly improved. Results illustrate the value of the design process in concurrently evaluating the relative costs/benefits of various liner designs. This study also provides further confidence in the integrated use of duct acoustic propagation/radiation and liner modeling tools in the design and evaluation of novel broadband liner concepts for complex engine configurations.

Nark, Douglas M.↗

Remote Sensing Time Series Product Tool

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

Predos, Don↗

Noise and Dynamical Pattern Selection in Solidification

The overall goal of this project was to understand in more detail how a pattern-forming system can adjust its spacing. "Pattern-forming systems," in this context, are nonequilibrium contina whose state is determined by experimentally adjustable control parameter. Below some critical value of the control system then has available to it a range of linearly stable, spatially periodic steady states, each characterized by a spacing which can lie anywhere within some band of values. These systems like directional solidification, where the solidification front is planar when the ratio of growth velocity to thermal gradient is below its critical value, but takes on a cellular shape above critical. They also include systems without interfaces, such as Benard convection, where it is the fluid velocity field which changes from zero to something spatially periodic as the control parameter is increased through its critical value. The basic question to be addressed was that of how the system chooses one of its myriad possible spacings when the control parameter is above critical, and in particular the role of noise in the selection process. Previous work on explosive crystallization had suggested that one spacing in the range should be preferred, in the sense that weak noise should eventually drive the system to that spacing. That work had also suggested a heuristic argument for identifying the preferred spacing. The project had three main objectives: to understand in more detail how a pattern-forming system can adjust its spacing; to investigate how noise drives a system to its preferred spacing; and to extend the heuristic argument for a preferred spacing in explosive crystallization to other pattern-forming systems.

Kurtze, Douglas A.↗

Detection in fixed and random noise in foveal and parafoveal vision explained by template learning

Foveal and parafoveal contrast detection thresholds for Gabor and checkerboard targets were measured in white noise by means of a two-interval forced-choice paradigm. Two white-noise conditions were used: fixed and twin. In the fixed noise condition a single noise sample was presented in both intervals of all the trials. In the twin noise condition the same noise sample was used in the two intervals of a trial, but a new sample was generated for each trial. Fixed noise conditions usually resulted in lower thresholds than twin noise. Template learning models are presented that attribute this advantage of fixed over twin noise either to fixed memory templates' reducing uncertainty by incorporation of the noise or to the introduction, by the learning process itself, of more variability in the twin noise condition. Quantitative predictions of the template learning process show that it contributes to the accelerating nonlinear increase in performance with signal amplitude at low signal-to-noise ratios.

NASA Center ARC↗