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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 955 records · Page 53

Characterization and Uncertainty Analysis of a Reference Pressure Measurement System for Wind Tunnels

This paper presents the calibration results and uncertainty analysis of a high-precision reference pressure measurement system currently used in wind tunnels at the NASA Langley Research Center (LaRC). Sensors, calibration standards, and measurement instruments are subject to errors due to aging, drift with time, environment effects, transportation, the mathematical model, the calibration experimental design, and other factors. Errors occur at every link in the chain of measurements and data reduction from the sensor to the final computed results. At each link of the chain, bias and precision uncertainties must be separately estimated for facility use, and are combined to produce overall calibration and prediction confidence intervals for the instrument, typically at a 95% confidence level. The uncertainty analysis and calibration experimental designs used herein, based on techniques developed at LaRC, employ replicated experimental designs for efficiency, separate estimation of bias and precision uncertainties, and detection of significant parameter drift with time. Final results, including calibration confidence intervals and prediction intervals given as functions of the applied inputs, not as a fixed percentage of the full-scale value are presented. System uncertainties are propagated beginning with the initial reference pressure standard, to the calibrated instrument as a working standard in the facility. Among the several parameters that can affect the overall results are operating temperature, atmospheric pressure, humidity, and facility vibration. Effects of factors such as initial zeroing and temperature are investigated. The effects of the identified parameters on system performance and accuracy are discussed.

Amer, Tahani↗

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps incidents are attributed to human error. As a part of Quality within space exploration ground processing operations, the identification and or classification of underlying contributors and causes of human error must be identified, in order to manage human error.This presentation will provide a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

human error↗

Long-Term Changes/Trends in Surface Temperature and Precipitation During the Satellite Era (1979-2012)

During the post-1979 period in which the satellite-based precipitation measurements with global coverage are available, global mean surface temperature rapidly increased up to late 1990s, followed by a period of temperature hiatus after about 19981999. Comparing observed surface temperature trends against the simulated ones by the CMIP5 historical experiments especially in the zonal mean context suggests that although the anthropogenic greenhouse-gases (GHG) forcing has played a major role, in addition to the anthropogenic aerosols and various natural forcings, the effects from decadal-to-interdecadal scale internal modes specifically the Pacific Decadal Oscillation(PDO) are also very strong. Evident temperature changes associated with the PDOs phase shift are seen in the Pacific basin, with decadal-scale cooling in the tropical central-eastern Pacific and most of the east basin and concurrent warming in the subtropics of both hemispheres,even though the PDOs net effect on global mean temperature is relatively weak. The Atlantic Multidecadal Oscillation(AMO) also changed its phase in the mid-1990s, and hence its possible impact is estimated and assessed as well.However, comparisons with CMIP5 simulations suggest that the AMO may have not contributed as significantly as the PDO in terms of the changes trends in global surface temperature, even though the data analysis technique used here suggests otherwise. Long-term precipitation changes or trends during the post-1979 period are further shown to have been modulated by the two major factors:anthropogenic GHG and PDO, in addition to the relatively weak effects from aerosols and natural forcings. The spatial patterns of observed precipitation trends in the Pacific,including reductions in the tropical central-eastern Pacific and increases in the tropical western Pacific and along the South Pacific Convergence Zone, manifest the PDOs contributions.Removing the PDO effect from the total precipitation trends makes the spatial structures of precipitation trends more similar to those simulated by CMIP5 historical full forcing experiments particularly in the context of zonal-mean results. This also confirms that in spite of the PDO effect specifically on regional scales, the anthropogenic GHG signals are still discernible in observed precipitation during the time period. Following the increase of GHG, precipitation tends to increase roughly along the climatological ITCZ and decrease south of the equator and in the subtropics of both hemispheres.

GPCP↗

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps/incidents are attributed to human error. As a part of Safety within space exploration ground processing operations, the identification and/or classification of underlying contributors and causes of human error must be identified, in order to manage human error. This research provides a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

human error↗

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps incidents are attributed to human error. As a part of Safety within space exploration ground processing operations, the identification and/or classification of underlying contributors and causes of human error must be identified, in order to manage human error. This research provides a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

mishaps↗

Microstructure Segmentation with Deep Learning Encoders Pre-Trained on a Large Microscopy Dataset

This study examined the improvement of microscopy segmentation accuracy by transfer learning from a large dataset of microscopy images called MicroNet. Many neural network encoder architectures, including VGG, Inception, and ResNet, were trained on over 100,000 labelled microscopy images from 54 classes. These pre-trained encoders were then embedded into multiple segmentation architectures including U-Net and DeepLabV3+ to evaluate segmentation performance on newly created benchmark microscopy datasets. Compared to ImageNet pre-training, models pre-trained on MicroNet generalized better to out-of-distribution micrographs taken under different imaging and sample conditions and were more accurate with less training data. When training with only a single Ni-superalloy image, pre-training on MicroNet produced a 72.2 percent reduction in relative segmentation error. These results suggest that transfer learning from large in-domain datasets generate models with learned feature representations that are more useful for downstream tasks and will likely improve any microscopy image analysis technique that can leverage pre-trained encoders.

machine learning↗

Investigation of Injector Slot Geometry on Curved-Diffuser Aerodynamic Performance

The Compressor Branch vision is to be recognized as world-class leaders in research for fluid mechanics of compressors. Its mission is to conduct research and develop technology to advance the state of the art of compressors and transfer new technology to U.S. industries. Maintain partnerships with U.S. industries, universities, and other government organizations. Maintain a balance between customers focused and long range research. Flow control comprises enabling technologies to meet compression system performance requirements driven by emissions and fuel reduction goals (e.g., in UEET), missions (e.g., access-to-space), aerodynamically aggressive vehicle configurations (e.g., UAV and future blended wing body configurations with highly distorted inlets), and cost goals (e.g., in VAATE). The compression system requirements include increased efficiency, power-to-weight, and adaptability (i.e., robustness in terms of wide operability, distortion tolerance, and engine system health and reliability). The compressor flow control task comprises efforts to develop, demonstrate, and transfer adaptive flow control technology to industry to increase aerodynamic loading at current blade row loss levels, to enable adaptive1 y wide operability, and to develop plant models for adaptive compression systems. In this context, flow control is the controlled modification of a flow field by a deliberate means beyond the natural (uncontrolled) shaping of the solid surfaces that define the principal flow path. The objective of the compressor flow control task is to develop and apply techniques that control circulation, aerodynamic blockage, and entropy production in order to enhance the performance and operability of compression systems for advanced aero-propulsion applications. This summer I would be working with a curved-diffuser because it simulates what happens with flow in the stator blades in the compressor. With this experiment I will be doing some data analysis and parametric study of the injector slot geometries to get the best aerodynamic performance of it. This includes some data reduction, redesign and fast prototyping of the injector nozzle.

Silva, Odlanier↗

Application of a Metal Artifact Reduction Algorithm for C-Arm Cone-Beam CT: Impact on Image Quality and Diagnostic Confidence for Bronchial Artery Embolization

Objective: The objective of this study was to evaluate the potential benefit of a dedicated cone-beam-CT streak metal artifact removal technique (SMART) in terms of both image quality and diagnostic confidence in patients undergoing bronchial artery embolization. Methods: A total of 17 patients were included in this retrospective study. The SMART algorithm was applied to images containing streak artifacts generated by a radiopaque intra-arterial catheter tip. Quantitative evaluation of artifact severity was performed via measurement of the Hounsfield units along a closed loop surrounding the catheter tip and was conducted in the frequency domain following the application of the discrete Fourier transform to the measured data. A high proportion of power in the low frequencies of the resulting spectrum indicated a high level of streak artifacts. Qualitative evaluation of diagnostic confidence was performed using a 4-point Likert scale. Results: Both quantitative and qualitative evaluation demonstrated a significant reduction in artifact severity using the SMART algorithm. Quantitative evaluation demonstrated a mean artifact reduction of 22.5% using SMART compared to non-SMART images (p < 0.001). Qualitative evaluation demonstrated the greatest artifact reduction at the inner and outer aortic curvature, as well as immediately surrounding the tip of the catheter. In 6 of 17 cases, the use of the SMART algorithm yielded additional clinical information, increasing mean diagnostic confidence from 3.17 to 3.78 (p < 0.001). Conclusion: The SMART algorithm allows for efficient reduction of metal artifacts introduced by radiopaque catheter tips during cone-beam CT. Using this algorithm, diagnostic images of the aortic arch were significantly improved both quantitatively and qualitatively, yielding clinically relevant levels of enhanced diagnostic confidence. These results demonstrate that the SMART algorithm improves diagnostic and clinical characterization of the course of bronchial arteries on CBCT images, potentially improving the accuracy and clinical efficacy of bronchial artery embolization. Level of Evidence: 3.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

An overview of wind-energy-production prediction bias, losses, and uncertainties

Abstract. The financing of a wind farm directly relates to the preconstruction energy yield assessments which estimate the annual energy production for the farm. The accuracy and the precision of the preconstruction energy estimates can dictate the profitability of the wind project. Historically, the wind industry tended to overpredict the annual energy production of wind farms. Experts have been dedicated to eliminating such prediction errors in the past decade, and recently the reported average energy prediction bias is declining. Herein, we present a literature review of the energy yield assessment errors across the global wind energy industry. We identify a long-term trend of reduction in the overprediction bias, whereas the uncertainty associated with the prediction error is prominent. We also summarize the recent advancements of the wind resource assessment process that justify the bias reduction, including improvements in modeling and measurement techniques. Additionally, because the energy losses and uncertainties substantially influence the prediction error, we document and examine the estimated and observed loss and uncertainty values from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 wind resource assessment standard. From our findings, we highlight opportunities for the industry to move forward, such as the validation and reduction of prediction uncertainty and the prevention of energy losses caused by wake effect and environmental events. Overall, this study provides a summary of how the wind energy industry has been quantifying and reducing prediction errors, energy losses, and production uncertainties. Finally, for this work to be as reproducible as possible, we include all of the data used in the analysis in appendices to the article.

17 WIND ENERGY↗

Contemporary Trends in the Acid-Base Status of the Two Acid-Sensitive Streams in Western Maryland

Recovery of streamwater acid neutralizing capacity (ANC) resulting from declines in regional acid deposition was examined using contemporary (1990-2005) data from two long-term monitoring stations located on the Appalachian Plateau in western Maryland, U.S. Two computational methods were used to estimate daily, monthly, and annual fluxes and discharge-weighted concentrations of ANC, sulfate, nitrate, and base cations over the period of record, and two statistical methods were used to evaluate long-term trends in fluxes and concentrations. The methods used to estimate concentrations, as well as the, statistical techniques, produced very similar results, underlining the robustness of the identified trends. We found clear evidence that streamwater sulfate concentrations have declined at an average rate of about 3 (microns)eq L(exp -1) yr(exp -1) at the two sites due to a 34% reduction in wet atmospheric sulfur deposition. Trends in nitrate concentrations appear to be related to other watershed factors, especially forest disturbance. The best evidence of recovery is based on a doubling of ANC (from 21 to 42 (microns)eq L(exp -1) at the more acid-sensitive site over the 16-year period. A slowing, or possible reversal, in the sulfate, nitrate, and SBC trends is evident in our data and may portend a decline in the rate of--or end to--further recovery.

Eshleman, Keith N.↗

NASA research on structures and materials for supersonic cruise aircraft

The technology and data base necessary for sound technical decisions regarding long haul supersonic cruise aircraft transportation systems are considered. The objectives and status of the research elements in the structures and materials program phase of the program are reviewed. Emphasis is placed on reductions in structural mass by research on advanced structural concepts, light-weight materials, improved loads, aeroelastic predictive techniques, and by development of efficient structural design procedures.

Cooper, P. A.↗

NASA/BLM APT, phase 2. Volume 2: Technology demonstration

Techniques described include: (1) steps in the preprocessing of LANDSAT data; (2) the training of a classifier; (3) maximum likelihood classification and precision; (4) geometric correction; (5) class description; (6) digitizing; (7) digital terrain data; (8) an overview of sample design; (9) allocation and selection of primary sample units; (10) interpretation of secondary sample units; (11) data collection ground plots; (12) data reductions; (13) analysis for productivity estimation and map verification; (14) cost analysis; and (150) LANDSAT digital products. The evaluation of the pre-inventory planning for P.J. is included.

Source record↗

Development of a microcomputer-based magnetic heading sensor

This paper explores the development of a flux-gate magnetic heading reference using a single-chip microcomputer to process heading information and to present it to the pilot in appropriate form. This instrument is intended to replace the conventional combination of mechanical compass and directional gyroscope currently in use in general aviation aircraft, at appreciable savings in cost and reduction in maintenance. Design of the sensing element, the signal processing electronics, and the computer algorithms which calculate the magnetic heading of the aircraft from the magnetometer data have been integrated in such a way as to minimize hardware requirements and simplify calibration procedures. Damping and deviation errors are avoided by the inherent design of the device, and a technique for compensating for northerly-turning-error is described.

Garner, H. D.↗

Spur-reduced digital sinusoid synthesis

This article presents and analyzes a technique for reducing the spurious signal content in digital sinusoid synthesis. Spurious-harmonic (spur) reduction is accomplished through dithering both amplitude and phase values prior to word-length reduction. The analytical approach developed for analog quantization is used to produce new bounds on spur performance in these dithered systems. Amplitude dithering allows output word-length reduction without introducing additional spurs. Effects of periodic dither similar to those produced by a pseudonoise (PN) generator are analyzed. This phase-dithering method provides a spur reduction of 6(M plus one) dB per phase bit when the dither consists of M uniform variates. While the spur reduction is at the expense of an increase in system noise, the noise power can be made white, making the power spectral density small. This technique permits the use of a smaller number of phase bits addressing sinusoid lookup tables, resulting in an exponential decrease in system complexity. Amplitude dithering allows the use of less complicated multipliers and narrower data paths in purely digital applications, as well as the use of coarse resolution, highly linear digital to analog converters (DAC's) to obtain spur performance limited by the DAC linearity rather than its resolution.

Flanagan, M. J.↗

Application of DPIV to Enhanced Mixing Heated Nozzle Flows

Digital Particle Imaging Velocimetry (DPIV) is a planar velocity measurement technique that continues to be applied to new and challenging engineering research facilities while significantly reducing facility test time. DPIV was used in the GRC Nozzle Acoustic Test Rig (NATR) to characterize the high temperature (560 C), high speed (is greater than 500 m/s) flow field properties of mixing enhanced jet engine nozzles. The instantaneous velocity maps obtained using DPIV were used to determine mean velocity, rms velocity and two-point correlation statistics to verify the true turbulence characteristics of the flow. These measurements will ultimately be used to properly validate aeroacoustic model predictions by verifying CFD input to these models. These turbulence measurements have previously not been possible in hot supersonic jets. Mapping the nozzle velocity field using point based techniques requires over 60 hours of test time, compared to less than 45 minutes using DPIV, yielding a significant reduction in testing time. A dual camera DPIV configuration was used to maximize the field of view and further minimize the testing time required to map the nozzle flow. The DPIV system field of view covered 127 by 267 mm. Data were acquired at 19 axial stations providing coverage of the flow from the nozzle exit to 2.37 in downstream. At each measurement station, 400 image frame pairs were acquired from each camera. The DPIV measurements of the mixing enhanced nozzle designs illustrate the changes in the flow field resulting in the reduced noise signature.

Wernet, Mark P.↗

Microstructure Segmentation With Deep Learning Encoders Pre-Trained on a Large Microscopy Dataset

This study examined the improvement of microscopy segmentation intersection over union accuracy by transfer learning from a large dataset of microscopy images called MicroNet. Many neural network encoder architectures were trained on over 100,000 labeled microscopy images from 54 material classes. These pre-trained encoders were then embedded into multiple segmentation architectures including UNet and DeepLabV3+ to evaluate segmentation performance on created benchmark microscopy datasets. Compared to ImageNet pre-training, models pre-trained on MicroNet generalized better to out-of-distribution micrographs taken under different imaging and sample conditions and were more accurate with less training data. When training with only a single Ni-superalloy image, pre-training on MicroNet produced a 72.2% reduction in relative intersection over union error. These results suggest that transfer learning from large in-domain datasets generate models with learned feature representations that are more useful for downstream tasks and will likely improve any microscopy image analysis technique that can leverage pre-trained encoders.

machine learning↗

External Magnetic Field Reduction Techniques for the Advanced Stirling Radioisotope Generator

Linear alternators coupled to high efficiency Stirling engines are strong candidates for thermal-to-electric power conversion in space. However, the magnetic field emissions, both AC and DC, of these permanent magnet excited alternators can interfere with sensitive instrumentation onboard a spacecraft. Effective methods to mitigate the AC and DC electromagnetic interference (EMI) from solenoidal type linear alternators (like that used in the Advanced Stirling Convertor) have been developed for potential use in the Advanced Stirling Radioisotope Generator. The methods developed avoid the complexity and extra mass inherent in data extraction from multiple sensors or the use of shielding. This paper discusses these methods, and also provides experimental data obtained during breadboard testing of both AC and DC external magnetic field devices.

Thermoelectric Power Generation↗

Applying EVM to Satellite on Ground and In-Orbit Testing - Better Data in Less Time

Using Error Vector Magnitude (EVM) in satellite integration and test allows rapid verification of the Bit Error Rate (BER) performance of a satellite link and is particularly well suited to measurement of low bit rate satellite links where it can result in a major reduction in test time (about 3 weeks per satellite for the Geosynchronous Operational Environmental Satellite [GOES] satellites during ground test) and can provide diagnostic information. Empirical techniques developed to predict BER performance from EVM measurements and lessons learned about applying these techniques during GOES N, O, and P integration test and post launch testing, are discussed.

Peters, Robert↗