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At least 91 records · Page 5

Portable Health Algorithms Test System

A document discusses the Portable Health Algorithms Test (PHALT) System, which has been designed as a means for evolving the maturity and credibility of algorithms developed to assess the health of aerospace systems. Comprising an integrated hardware-software environment, the PHALT system allows systems health management algorithms to be developed in a graphical programming environment, to be tested and refined using system simulation or test data playback, and to be evaluated in a real-time hardware-in-the-loop mode with a live test article. The integrated hardware and software development environment provides a seamless transition from algorithm development to real-time implementation. The portability of the hardware makes it quick and easy to transport between test facilities. This hard ware/software architecture is flexible enough to support a variety of diagnostic applications and test hardware, and the GUI-based rapid prototyping capability is sufficient to support development execution, and testing of custom diagnostic algorithms. The PHALT operating system supports execution of diagnostic algorithms under real-time constraints. PHALT can perform real-time capture and playback of test rig data with the ability to augment/ modify the data stream (e.g. inject simulated faults). It performs algorithm testing using a variety of data input sources, including real-time data acquisition, test data playback, and system simulations, and also provides system feedback to evaluate closed-loop diagnostic response and mitigation control.

Melcher, Kevin J.↗

A Fast-Time Simulation Environment for Airborne Merging and Spacing Research

As part of NASA's Distributed Air/Ground Traffic Management (DAG-TM) effort, NASA Langley Research Center is developing concepts and algorithms for merging multiple aircraft arrival streams and precisely spacing aircraft over the runway threshold. An airborne tool has been created for this purpose, called Airborne Merging and Spacing for Terminal Arrivals (AMSTAR). To evaluate the performance of AMSTAR and complement human-in-the-loop experiments, a simulation environment has been developed that enables fast-time studies of AMSTAR operations. The environment is based on TMX, a multiple aircraft desktop simulation program created by the Netherlands National Aerospace Laboratory (NLR). This paper reviews the AMSTAR concept, discusses the integration of the AMSTAR algorithm into TMX and the enhancements added to TMX to support fast-time AMSTAR studies, and presents initial simulation results.

Bussink, Frank J. L.↗

Development of Jet Noise Power Spectral Laws

High-quality jet noise spectral data measured at the Aero-Acoustic Propulsion Laboratory (AAPL) at NASA Glenn is used to develop jet noise scaling laws. A FORTRAN algorithm was written that provides detailed spectral prediction of component jet noise at user-specified conditions. The model generates quick estimates of the jet mixing noise and the broadband shock-associated noise (BBSN) in single-stream, axis-symmetric jets within a wide range of nozzle operating conditions. Shock noise is emitted when supersonic jets exit a nozzle at imperfectly expanded conditions. A successful scaling of the BBSN allows for this noise component to be predicted in both convergent and convergent-divergent nozzles. Configurations considered in this study consisted of convergent and convergent- divergent nozzles. Velocity exponents for the jet mixing noise were evaluated as a function of observer angle and jet temperature. Similar intensity laws were developed for the broadband shock-associated noise in supersonic jets. A computer program called sJet was developed that provides a quick estimate of component noise in single-stream jets at a wide range of operating conditions. A number of features have been incorporated into the data bank and subsequent scaling in order to improve jet noise predictions. Measurements have been converted to a lossless format. Set points have been carefully selected to minimize the instability-related noise at small aft angles. Regression parameters have been scrutinized for error bounds at each angle. Screech-related amplification noise has been kept to a minimum to ensure that the velocity exponents for the jet mixing noise remain free of amplifications. A shock-noise-intensity scaling has been developed independent of the nozzle design point. The computer program provides detailed narrow-band spectral predictions for component noise (mixing noise and shock associated noise), as well as the total noise. Although the methodology is confined to single streams, efforts are underway to generate a data bank and algorithm applicable to dual-stream jets. Shock-associated noise in high-powered jets such as military aircraft can benefit from these predictions.

Khavaran, Abbas↗

A New Fast Algorithm to Completely Account for Non-Lambertian Surface Reflection of The Earth

Surface bidirectional reflectance distribution function (BRDF) influences not only radiance just about the surface, but that emerging from the top of the atmosphere (TOA). In this study we propose a new, fast and accurate, algorithm CASBIR (correction for anisotropic surface bidirectional reflection) to account for such influences on radiance measured above TOA. This new algorithm is based on a 4-stream theory that separates the radiation field into direct and diffuse components in both upwelling and downwelling directions. This is important because the direct component accounts for a substantial portion of incident radiation under a clear sky, and the BRDF effect is strongest in the reflection of the direct radiation reaching the surface. The model is validated by comparison with a full-scale, vector radiation transfer model for the atmosphere-surface system. The result demonstrates that CASBIR performs very well (with overall relative difference of less than one percent) for all solar and viewing zenith and azimuth angles considered in wavelengths from ultraviolet to near-infrared over three typical, but very different surface types. Application of this algorithm includes both accounting for non-Lambertian surface scattering on the emergent radiation above TOA and a potential approach for surface BRDF retrieval from satellite measured radiance.

Qin, Wen-Han↗

ICER-3D Hyperspectral Image Compression Software

Software has been developed to implement the ICER-3D algorithm. ICER-3D effects progressive, three-dimensional (3D), wavelet-based compression of hyperspectral images. If a compressed data stream is truncated, the progressive nature of the algorithm enables reconstruction of hyperspectral data at fidelity commensurate with the given data volume. The ICER-3D software is capable of providing either lossless or lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The compression algorithm, which was derived from the ICER image compression algorithm, includes wavelet-transform, context-modeling, and entropy coding subalgorithms. The 3D wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of sets of hyperspectral image data, while facilitating elimination of spectral ringing artifacts, using a technique summarized in "Improving 3D Wavelet-Based Compression of Spectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. Correlation is further exploited by a context-modeling subalgorithm, which exploits spectral dependencies in the wavelet-transformed hyperspectral data, using an algorithm that is summarized in "Context Modeler for Wavelet Compression of Hyperspectral Images" (NPO-43239), which follows this article. An important feature of ICER-3D is a scheme for limiting the adverse effects of loss of data during transmission. In this scheme, as in the similar scheme used by ICER, the spatial-frequency domain is partitioned into rectangular error-containment regions. In ICER-3D, the partitions extend through all the wavelength bands. The data in each partition are compressed independently of those in the other partitions, so that loss or corruption of data from any partition does not affect the other partitions. Furthermore, because compression is progressive within each partition, when data are lost, any data from that partition received prior to the loss can be used to reconstruct that partition at lower fidelity. By virtue of the compression improvement it achieves relative to previous means of onboard data compression, this software enables (1) increased return of hyperspectral scientific data in the presence of limits on the rates of transmission of data from spacecraft to Earth via radio communication links and/or (2) reduction in spacecraft radio-communication power and/or cost through reduction in the amounts of data required to be downlinked and stored onboard prior to downlink. The software is also suitable for compressing hyperspectral images for ground storage or archival purposes.

Xie, Hua↗

Online Power System Event Detection via Bidirectional Generative Adversarial Networks

Accurate and speedy detection of power system events is critical to enhancing the reliability and resiliency of power systems. Although supervised deep learning algorithms show great promise in identifying power system events, they require a large volume of high-quality event labels for training. This paper develops a bidirectional anomaly generative adversarial network (GAN)-based algorithm to detect power system events using streaming PMU data, which does not rely on a huge amount of event labels. By introducing conditional entropy constraint in the objective function of GAN and graph signal processing-based PMU sorting technique, our proposed algorithm significantly outperforms state-of-the-art event detection algorithms in terms of accuracy. To facilitate the adoption of the proposed algorithm, a prototype online platform is also developed using Apache Hadoop, Kafka, and Spark to enable real-time event detection. Here, the accuracy and computational efficiency of the proposed algorithm are validated using a large-scale real-world PMU dataset from the Eastern Interconnection of the United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Compression of multispectral Landsat imagery using the Embedded Zerotree Wavelet (EZW) algorithm

The Embedded Zerotree Wavelet (EZW) algorithm has proven to be an extremely efficient and flexible compression algorithm for low bit rate image coding. The embedding algorithm attempts to order the bits in the bit stream in numerical importance and thus a given code contains all lower rate encodings of the same algorithm. Therefore, precise bit rate control is achievable and a target rate or distortion metric can be met exactly. Furthermore, the technique is fully image adaptive. An algorithm for multispectral image compression which combines the spectral redundancy removal properties of the image-dependent Karhunen-Loeve Transform (KLT) with the efficiency, controllability, and adaptivity of the embedded zerotree wavelet algorithm is presented. Results are shown which illustrate the advantage of jointly encoding spectral components using the KLT and EZW.

Shapiro, Jerome M.↗

Signal-to-noise Ratio and Combiner Weight Estimation for Symbol Stream Combining

A method is presented for signal to noise ratio (SNR) and symbol stream combiner weight estimation. The SNR estimator employs absolute value moments as in an earlier method. The main contribution is that a new algorithm is derived for the combiner weight estimator to remove the large bias at low SNRs. The new algorithm is simulated to combine two independent symbol streams at various SNRs. As an example, the combining two symbol streams at SNRs of -1 dB and -7 dB, conbiner weight estimates using 1000 samples for the -1 dB stream and 10,000 samples for the -7 dB stream achieve an output SNR of -0.039 dB, which is just 0.012 dB below the theoretical limit achievable with perfect knowledge of the SNRs.

Vo, Q. D.↗

Constituent Data Replacement Tool

The purpose of this tool is to estimate key parameters that may be missing in public wastewater composition datasets. The tool can be applied to develop complete treatment and critical mineral extraction profiles for leachate, produced water and other aqueous waste streams. The tool applies machine learning algorithms to replace missing data in a user’s water data set that are adjusted based on user preferences for options including algorithm type, number of features, and classification variables. The tool can use the user’s data alone or combine user data with the NEWTS USGS Produced Water Database for more robust training. This research was funded by the U.S. Department of Energy’s Office Fossil Energy and Carbon Management (FECM) through National Energy Technology Laboratory’s ongoing research under the Water Management for Power System Field Work Proposal, DE-FECM 1022428 and Critical Minerals Field Work Proposal, DE-FECM 1022420.

Aqueous Chemistry↗

Energy-Efficient Adaptive Cruise Control Using Eco-Driving Algorithm

SwRI Eco-Driving Algorithm – Objectives and Method – Required Information Streams and Velocity Profile Realization ▪ Impact on Energy Consumption – Study 1 – NEXTCAR II • Individual (ego/eco) vehicle on Blanco Road, San Antonio, TX – Study 2 – DOE EEMS • Entire Urban Corridor – N High Street, Columbus, OH

Bhagdikar, Piyush↗

RICH (Robotic Interface Control & Handling) System for VULCAN

High flux neutron beam and high efficiency detectors warrant quick turn arounds of neutron diffraction measurements at the engineering materials diffractometer VULCAN. Efficient change and alignment of samples and automatic measurements at VULCAN are desired for better use of neutron beam time by users. In this work, we aim to develop a proof-of-concept Robotic Interactive Control & Handling System (RICH) for sample handling at VULCAN that could assist high throughput experiments and reduce the overhead time significantly. This was realized by a six-axis desktop robot with trained AI models. The trained AI models can recognize and locate samples in various types of positions in a live video stream. In addition, we developed smart algorithms which used our models on multiple cameras to recognize where samples are with respect to multiple point of views, and then using user-inputted parameters, align them to perform complex measurements.

42 ENGINEERING↗

The IRAS faint source survey

The principal features of the IRAS Faint Source Survey (FSS), a new product resulting from the extended IRAS mission, are reviewed. The FSS has achieved an increase in sensitivity of about a factor of 2.5 relative to the IRAS Point Source Catalog by coadding the data before extracting sources. The FSS was produced by point-source filtering the individual detector data streams and then coadding the data streams using a trimmed-average algorithm. The discussion covers FSS production methods; reliability, completeness, and positional accuracy of the FSS; and FSS view of the IR sky.

Moshir, Mehrdad↗

Distributed Framework for Dynamic Telescope and Instrument Control

Traditionally, instrument command and control systems have been developed specifically for a single instrument. Such solutions are frequently expensive and are inflexible to support the next instrument development effort. NASA Goddard Space Flight Center is developing an extensible framework, known as Instrument Remote Control (IRC) that applies to any kind of instrument that can be controlled by a computer. IRC combines the platform independent processing capabilities of Java with the power of the Extensible Markup Language (XML). A key aspect of the architecture is software that is driven by an instrument description, written using the Instrument Markup Language (IML). IML is an XML dialect used to describe graphical user interfaces to control and monitor the instrument, command sets and command formats, data streams, communication mechanisms, and data processing algorithms. The IRC framework provides the ability to communicate to components anywhere on a network using the JXTA protocol for dynamic discovery of distributed components. JXTA (see httD://www.jxta.org,) is a generalized protocol that allows any devices connected by a network to communicate in a peer-to-peer manner. IRC uses JXTA to advertise a device's IML and discover devices of interest on the network. Devices can join or leave the network and thus join or leave the instrument control environment of IRC. Currently, several astronomical instruments are working with the IRC development team to develop custom components for IRC to control their instruments. These instruments include: High resolution Airborne Wideband Camera (HAWC), a first light instrument for the Stratospheric Observatory for Infrared Astronomy (SOFIA); Submillimeter And Far Infrared Experiment (SAFIRE), a Principal Investigator instrument for SOFIA; and Fabry-Perot Interferometer Bolometer Research Experiment (FIBRE), a prototype of the SAFIRE instrument, used at the Caltech Submillimeter Observatory (CSO). Most recently, we have been working with the Submillimetre High Angular Resolution Camera IInd Generation (SHARCII) at the CSO to investigate using IRC capabilities with the SHARC instrument.

Ames, Troy J.↗

XML in an Adaptive Framework for Instrument Control

NASA Goddard Space Flight Center is developing an extensible framework for instrument command and control, known as Instrument Remote Control (IRC), that combines the platform independent processing capabilities of Java with the power of the Extensible Markup Language (XML). A key aspect of the architecture is software that is driven by an instrument description, written using the Instrument Markup Language (IML). IML is an XML dialect used to describe interfaces to control and monitor the instrument, command sets and command formats, data streams, communication mechanisms, and data processing algorithms.

Ames, Troy J.↗

Processing Ocean Images to Detect Large Drift Nets

A computer program processes the digitized outputs of a set of downward-looking video cameras aboard an aircraft flying over the ocean. The purpose served by this software is to facilitate the detection of large drift nets that have been lost, abandoned, or jettisoned. The development of this software and of the associated imaging hardware is part of a larger effort to develop means of detecting and removing large drift nets before they cause further environmental damage to the ocean and to shores on which they sometimes impinge. The software is capable of near-realtime processing of as many as three video feeds at a rate of 30 frames per second. After a user sets the parameters of an adjustable algorithm, the software analyzes each video stream, detects any anomaly, issues a command to point a high-resolution camera toward the location of the anomaly, and, once the camera has been so aimed, issues a command to trigger the camera shutter. The resulting high-resolution image is digitized, and the resulting data are automatically uploaded to the operator s computer for analysis.

Veenstra, Tim↗

Fast Data Processing for Hyperspectral Sensors on Small Platforms

Hyperspectral imaging is a very promising technology for nuclear proliferation detection. However, due to size and weight restrictions, small hyperspectral platforms such as satellites and small drones lack the on-board computing resources for accurate, real-time analysis of the enormous flow of data that a continuously operating hyperspectral sensor generates. This severely limits satellite systems, which can collect far more data than what they can telemeter, and hinders the ability of all platforms to adapt their missions on the fly in response to observations. This program addresses the hyperspectral data processing challenge through development of new, fast and accurate algorithms that produce data products in real time. The algorithms circumvent the major computational bottlenecks in existing processing streams, and would be incorporated in lightweight, power-efficient single-board computer systems. The toolkit of fast algorithms will be immediately useful in current and future hyperspectral systems being built by the Government and by private industry, including drone-based systems and satellite constellations that acquire timely global imagery.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Cloud Scattering Impact on Thermal Radiative Transfer and Global Longwave Radiation

The potential importance of longwave (LW) cloud scattering has been recognized but the actual estimate of this effect on thermal radiation varies greatly among different studies. General circulation models (GCMs) generally neglect or simplify the multiple scattering in the LW. In this study, we use a rigorous radiative transfer algorithm to explicitly consider LW multiple-scattering and apply the GCM to quantify the impact of cloud LW scattering on thermal radiation fluxes. Our study shows that the cloud scattering effect on downward thermal radiation at the surface is concentrated in the infrared atmospheric window spectrum (800–1250 cm9exp −1)). The scattering effect on the outgoing longwave radiation (OLR) is also present in the window region over low clouds but it is mainly in the far-infrared spectrum (300–600 cm(exp −1)) over high clouds. For clouds with small to moderate optical depth (τ < 10), the scattering effect on thermal fluxes shows large variation with the cloud τ and has a maximum at an optical depth of ∼3. For opaque clouds, the scattering effect approaches an asymptote and is smaller and less important. The 2-stream radiative transfer scheme could have an error over 10% with an RMS error around 3.5%–4.0% in the calculated LW flux. This algorithm error of the 2-stream approximation could readily exceed the no-scattering error in the LW, and thus it is worthless to include the time-consuming computation of multiple scattering in a 2-stream radiative transfer scheme. However, the calculation error rapidly decreases as stream number increases and the RMS error in LW flux using the 4-stream scheme is under 0.3%, an accuracy sufficient for most climate studies. We implement the 4-stream discrete-ordinate algorithm in the GISS GCM and run the GCM for 20 years with and without the LW scattering effect, respectively. When cloud LW scattering is included, we find that the global annual mean OLR is reduced by 2.7 W/m(exp 2), and the downward surface flux and the net atmospheric absorption are increased by 1.6 W/m2 and 1.8 W/m(exp 2), respectively. Using one year of ISCCP clouds and running the standalone radiative transfer offline, the global annual mean non-scattering errors in OLR, surface LW downward flux and net atmospheric absorption are 3.6 W/m(exp 2), −1.1 W/m(exp 2), and −2.5 W/m(exp 2), respectively. The global scattering impact of 2.7 W/m(exp 2) on the OLR is small when compared to the typical global OLR value of 240 W/m2, but it is significant when compared to cloud LW radiative forcing (30 W/m2) and net cloud forcing (−14 W/m(exp 2)). Overall, the effect of neglecting scattering on the thermal fluxes is comparable to the reported clear sky radiative effect of doubling CO2.

longwave cloud scattering↗