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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Noise Reduction Technologies for Turbofan Engines

Significant progress continues to be made with noise reduction for turbofan engines. NASA has conducted and sponsored research aimed at reducing noise from commercial aircraft. Since it takes many years for technologies to be developed and implemented, it is important to have aggressive technology goals that lead the target entry into service dates. Engine noise is one of the major contributors to the overall sound levels as aircraft operate near airports. Turbofan engines are commonly used on commercial transports due to their advantage for higher performance and lower noise. The noise reduction comes from combinations of changes to the engine cycle parameters and low noise design features. In this paper, an overview of major accomplishments from recent NASA research programs for engine noise will be given.

Huff, Dennis L.↗
DOE OSTI2026

Effect of outer divertor leg detachment on the high field side scrape-off layer in DIII-D and ASDEX Upgrade

In this work, evidence is presented that detachment of the outer divertor leg leads to a reduction of electron density and neutral pressure in the high-field side (HFS) scrape-off layer (SOL) of the ASDEX Upgrade (AUG) and DIII-D tokamaks with ion $B$ x $∇B$ drift directed toward the X-point (favorable configuration). These results are observed across multiple diagnostics and without the use of impurity seeding to reach detachment. In AUG, outer divertor leg detachment correlates with a decrease in electron density near the separatrix at the inner midplane, measured with HFS reflectometry. A concurrent reduction in inner divertor density and neutral pressure at the inner target is observed using divertor Thomson scattering and neutral pressure gauges. These effects are present in both L- and H-mode plasmas. In DIII-D, a similar reduction is detected through analysis of line-integrated hydrogenic emission measured by multiple diagnostics in the HFS SOL close to the separatrix. The consistent trends in both devices indicate that high electron density and strong hydrogenic emissivity in the HFS SOL are common features of H-mode plasmas in the favorable configuration, independent of wall material and divertor geometry. In L-mode plasmas, the reduction in electron density and neutral pressure is not observed in DIII-D, possibly due to differences in wall material. These results emphasize the importance of the divertor state in determining the two-dimensional neutral distribution and edge fueling.

detachment↗
NASA NTRS2019

High Efficiency Megawatt Motor Preliminary Design

The High Efficiency Megawatt Motor (HEMM) is being designed to meet the needs of Electrified Aircraft Propulsion (EAP). A preliminary design has been completed and risk reduction activities are being conducted in three key areas: cryogenic cooler design, superconducting rotor coil design and manufacturing, and stator thermal management. The key objective of HEMM is to establish a motor technology which simultaneously attains high specific power (>16kW/kg ratio to electromagnetic weight) and high efficiency (>98%) by judicious application of high temperature superconducting wire and integrated thermal management. Another important feature is to achieve the performance goals with an eye to aircraft integration constraints. An electromagnetic analysis was performed which shows that the proposed HEMM design meets the performance objectives if key current capability and mechanical constraints are achieved. The risk reduction activities are the first assessment of the key design features. The HEMM technology could be applied to a range of aircraft types that require megawatt level electrical power.

Jansen, Ralph H.↗
NASA NTRS2007

Workshop on Jet Exhaust Noise Reduction for Tactical Aircraft - NASA Perspective

Jet noise from supersonic, high performance aircraft is a significant problem for takeoff and landing operations near air bases and aircraft carriers. As newer aircraft with higher thrust and performance are introduced, the noise tends to increase due to higher jet exhaust velocities. Jet noise has been a subject of research for over 55 years. Commercial subsonic aircraft benefit from changes to the engine cycle that reduce the exhaust velocities and result in significant noise reduction. Most of the research programs over the past few decades have concentrated on commercial aircraft. Progress has been made by introducing new engines with design features that reduce the noise. NASA has recently started a new program called "Fundamental Aeronautics" where three projects (subsonic fixed wing, subsonic rotary wing, and supersonics) address aircraft noise. For the supersonics project, a primary goal is to understand the underlying physics associated with jet noise so that improved noise prediction tools and noise reduction methods can be developed for a wide range of applications. Highlights from the supersonics project are presented including prediction methods for broadband shock noise, flow measurement methods, and noise reduction methods. Realistic expectations are presented based on past history that indicates significant jet noise reduction cannot be achieved without major changes to the engine cycle. NASA s past experience shows a few EPNdB (effective perceived noise level in decibels) can be achieved using low noise design features such as chevron nozzles. Minimal thrust loss can be expected with these nozzles (< 0.5%) and they may be retrofitted on existing engines. In the long term, it is desirable to use variable cycle engines that can be optimized for lower jet noise during takeoff operations and higher thrust for operational performance. It is also suggested that noise experts be included early in the design process for engine nozzle systems to participate in decisions that may impact the jet noise.

Huff, Dennis L.↗
NASA NTRS2002

Investigation of Error Patterns in Geographical Databases

The objective of the research conducted in this project is to develop a methodology to investigate the accuracy of Airport Safety Modeling Data (ASMD) using statistical, visualization, and Artificial Neural Network (ANN) techniques. Such a methodology can contribute to answering the following research questions: Over a representative sampling of ASMD databases, can statistical error analysis techniques be accurately learned and replicated by ANN modeling techniques? This representative ASMD sample should include numerous airports and a variety of terrain characterizations. Is it possible to identify and automate the recognition of patterns of error related to geographical features? Do such patterns of error relate to specific geographical features, such as elevation or terrain slope? Is it possible to combine the errors in small regions into an error prediction for a larger region? What are the data density reduction implications of this work? ASMD may be used as the source of terrain data for a synthetic visual system to be used in the cockpit of aircraft when visual reference to ground features is not possible during conditions of marginal weather or reduced visibility. In this research, United States Geologic Survey (USGS) digital elevation model (DEM) data has been selected as the benchmark. Artificial Neural Networks (ANNS) have been used and tested as alternate methods in place of the statistical methods in similar problems. They often perform better in pattern recognition, prediction and classification and categorization problems. Many studies show that when the data is complex and noisy, the accuracy of ANN models is generally higher than those of comparable traditional methods.

Dryer, David↗
NASA NTRS2014

Structural Performance of Advanced Composite Tow-Steered Shells With Cutouts

The structural performance of two advanced composite tow-steered shells with cutouts, manufactured using an automated fiber placement system, is assessed using both experimental and analytical methods. The shells' fiber orientation angles vary continuously around their circumference from +/-10 degrees on the crown and keel, to +/-45 degrees on the sides. The raised surface features on one shell result from application of all 24 tows during each fiber placement system pass, while the second shell uses the system's tow drop/add capability to achieve a more uniform wall thickness. These unstiffened shells were previously tested in axial compression and buckled elastically. A single cutout, scaled to represent a passenger door on a commercial aircraft, is then machined into one side of each shell. The prebuckling axial stiffnesses and bifurcation buckling loads of the shells with cutouts are also computed using linear finite element structural analyses for initial comparisons with test data. When retested, large deflections were observed around the cutouts, but the shells carried an average of 92 percent of the axial stiffness, and 86 percent of the buckling loads, of the shells without cutouts. These relatively small reductions in performance demonstrate the potential for using tow steering to mitigate the adverse effects of typical design features on the overall structural performance.

Wu, K. Chauncey↗
DOE OSTI2023

Unsupervised classification for region of interest in X-ray ptychography

X-ray ptychography offers high-resolution imaging of large areas at a high computational cost due to the large volume of data provided. To address the cost issue, we propose a physics-informed unsupervised classification algorithm that is performed prior to reconstruction and removes data outside the region of interest (RoI) based on the multimodal features present in the diffraction patterns. The preprocessing time for the proposed method is inconsequential in contrast to the resource-intensive reconstruction process, leading to an impressive reduction in the data workload to a mere 20% of the initial dataset. This capability consequently reduces computational time dramatically while preserving reconstruction quality. Through further segmentation of the diffraction patterns, our proposed approach can also detect features that are smaller than beam size and correctly classify them as within the RoI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Evaluation of Extreme Weather Impacts on Utility-scale Photovoltaic Plant Performance in the United States

The global energy system is undergoing significant changes, including a shift in energy generating technologies to more renewable energy sources. However, the dependence of renewable energy sources on local environmental conditions could also increase disruptions in service through exposures to compound, extreme weather events. By fusing three diverse datasets (operations and maintenance tickets, weather data, and production data), this analysis presents a novel methodology to identify and evaluate performance impacts arising from extreme weather events across diverse geographical regions. Text analysis of maintenance tickets identified snow, hurricanes, and storms as the leading extreme weather events affecting photovoltaic plants in the United States. Statistical techniques and machine learning were then implemented to identify the magnitude and variability of these extreme weather impacts on site performance. Impacts varied between event and non-event days, with snow events causing the greatest reductions in performance (54.5%), followed by hurricanes (12.6%) and storms (1.1%). Machine learning analysis identified key features in determining if a day is categorized as low performing, such as low irradiance, geographic location, weather features, and site size. The analysis improves our understanding of compound, extreme weather event impacts on photovoltaic systems, which can inform planning activities, especially as the industry continues to expand into new geographic and climatic regions around the world.

14 SOLAR ENERGY↗
DOE OSTI2022

Radical Polymer-Based Organic Electrochemical Transistors

Organic electrochemical transistors (OECTs) are an emerging platform for bioelectronic applications. Significant effort has been placed in designing advanced polymers that simultaneously transport both charge and ions (i.e., macromolecules that are mixed conductors). Furthermore, the considerations for mixed organic conductors are often different from the established principles that are well-known in the solid-state organic electronics field; thus, the discovery of new OECT macromolecular systems is highly desired. Here, we demonstrate a new materials system by blending a radical polymer (i.e., a macromolecule with a nonconjugated backbone and with stable open-shell sites at its pendant group) with a frequently used conjugated polymer. Specifically, poly(4-glycidyloxy-2,2,6,6-tetramethylpiperidine-1-oxyl) (PTEO) was blended with poly(3-hexylthiophene) (P 3 HT) to create thin films with distinct closed-shell and open-shell domains. Importantly, the sharp and unique oxidation–reduction (redox) potential associated with the radical moieties of the PTEO chain provided a distinct actuation feature to the blended films that modulated the ionic transport of the OECT devices. In turn, this led to controlled regulation of the doping of the P 3 HT phase in the composite film. By decoupling the ionic and electronic transport into two distinct phases and by using an ion transport phase with well-controlled redox activity, never-before-seen performance for a P3HT-based OECT was observed. That is, at loadings as low as 5% PTEO (by weight) OECTs achieved figure-of-merit (i.e., μC*) values >150 F V –1 cm –1 s –1 , which place the performance on the same order as state-of-the-art conjugated polymers despite the relatively common conjugated macromolecular moiety implemented. As such, this effort presents a design platform by which to readily create a tailored OECT response through strategic macromolecular selection and polymer processing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Budget constrained machine learning for early prediction of adverse outcomes for COVID-19 patients

Abstract The combination of machine learning (ML) and electronic health records (EHR) data may be able to improve outcomes of hospitalized COVID-19 patients through improved risk stratification and patient outcome prediction. However, in resource constrained environments the clinical utility of such data-driven predictive tools may be limited by the cost or unavailability of certain laboratory tests. We leveraged EHR data to develop an ML-based tool for predicting adverse outcomes that optimizes clinical utility under a given cost structure. We further gained insights into the decision-making process of the ML models through an explainable AI tool. This cohort study was performed using deidentified EHR data from COVID-19 patients from ProMedica Health System in northwest Ohio and southeastern Michigan. We tested the performance of various ML approaches for predicting either increasing ventilatory support or mortality. We performed post hoc analysis to obtain optimal feature sets under various budget constraints. We demonstrate that it is possible to achieve a significant reduction in cost at the expense of a small reduction in predictive performance. For example, when predicting ventilation, it is possible to achieve a 43% reduction in cost with only a 3% reduction in performance. Similarly, when predicting mortality, it is possible to achieve a 50% reduction in cost with only a 1% reduction in performance. This study presents a quick, accurate, and cost-effective method to evaluate risk of deterioration for patients with SARS-CoV-2 infection at the time of clinical evaluation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

AIS-2 radiometry and a comparison of methods for the recovery of ground reflectance

A field experiment and its results involving Airborne Imaging Spectrometer-2 data are described. The radiometry and spectral calibration of the instrument are critically examined in light of laboratory and field measurements. Three methods of compensating for the atmosphere in the search for ground reflectance are compared. It was found that laboratory determined responsitivities are 30 to 50 percent less than expected for conditions of the flight for both short and long wavelength observations. The combined system atmosphere surface signal to noise ratio, as indexed by the mean response divided by the standard deviation for selected areas, lies between 40 and 110, depending upon how scene averages are taken, and is 30 percent less for flight conditions than for laboratory. Atmospheric and surface variations may contribute to this difference. It is not possible to isolate instrument performance from the present data. As for methods of data reduction, the so-called scene average or log-residual method fails to recover any feature present in the surface reflectance, probably because of the extreme homogeneity of the scene.

Conel, James E.↗
NASA NTRS2005

Development and Application of Non-Linear Image Enhancement and Multi-Sensor Fusion Techniques for Hazy and Dark Imaging

The purpose of this research was to develop enhancement and multi-sensor fusion algorithms and techniques to make it safer for the pilot to fly in what would normally be considered Instrument Flight Rules (IFR) conditions, where pilot visibility is severely restricted due to fog, haze or other weather phenomenon. We proposed to use the non-linear Multiscale Retinex (MSR) as the basic driver for developing an integrated enhancement and fusion engine. When we started this research, the MSR was being applied primarily to grayscale imagery such as medical images, or to three-band color imagery, such as that produced in consumer photography: it was not, however, being applied to other imagery such as that produced by infrared image sources. However, we felt that it was possible by using the MSR algorithm in conjunction with multiple imaging modalities such as long-wave infrared (LWIR), short-wave infrared (SWIR), and visible spectrum (VIS), we could substantially improve over the then state-of-the-art enhancement algorithms, especially in poor visibility conditions. We proposed the following tasks: 1) Investigate the effects of applying the MSR to LWIR and SWIR images. This consisted of optimizing the algorithm in terms of surround scales, and weights for these spectral bands; 2) Fusing the LWIR and SWIR images with the VIS images using the MSR framework to determine the best possible representation of the desired features; 3) Evaluating different mixes of LWIR, SWIR and VIS bands for maximum fog and haze reduction, and low light level compensation; 4) Modifying the existing algorithms to work with video sequences. Over the course of the 3 year research period, we were able to accomplish these tasks and report on them at various internal presentations at NASA Langley Research Center, and in presentations and publications elsewhere. A description of the work performed under the tasks is provided in Section 2. The complete list of relevant publications during the research periods is provided in Section 5. This research also resulted in the generation of intellectual property.

Rahman, Zia-ur↗
NASA NTRS1995

Cascade Optimization Strategy Maximizes Thrust for High-Speed Civil Transport Propulsion System Concept

The design of a High-Speed Civil Transport (HSCT) air-breathing propulsion system for multimission, variable-cycle operations was successfully optimized through a soft coupling of the engine performance analyzer NASA Engine Performance Program (NEPP) to a multidisciplinary optimization tool COMETBOARDS that was developed at the NASA Lewis Research Center. The design optimization of this engine was cast as a nonlinear optimization problem, with engine thrust as the merit function and the bypass ratios, r-values of fans, fuel flow, and other factors as important active design variables. Constraints were specified on factors including the maximum speed of the compressors, the positive surge margins for the compressors with specified safety factors, the discharge temperature, the pressure ratios, and the mixer extreme Mach number. Solving the problem by using the most reliable optimization algorithm available in COMETBOARDS would provide feasible optimum results only for a portion of the aircraft flight regime because of the large number of mission points (defined by altitudes, Mach numbers, flow rates, and other factors), diverse constraint types, and overall poor conditioning of the design space. Only the cascade optimization strategy of COMETBOARDS, which was devised especially for difficult multidisciplinary applications, could successfully solve a number of engine design problems for their flight regimes. Furthermore, the cascade strategy converged to the same global optimum solution even when it was initiated from different design points. Multiple optimizers in a specified sequence, pseudorandom damping, and reduction of the design space distortion via a global scaling scheme are some of the key features of the cascade strategy. HSCT engine concept, optimized solution for HSCT engine concept. A COMETBOARDS solution for an HSCT engine (Mach-2.4 mixed-flow turbofan) along with its configuration is shown. The optimum thrust is normalized with respect to NEPP results. COMETBOARDS added value in the design optimization of the HSCT engine.

Source record↗
NASA NTRS2011

Chlorophyll-a Algorithms for Oligotrophic Oceans: A Novel Approach Based on Three-Band Reflectance Difference

A new empirical algorithm is proposed to estimate surface chlorophyll-a concentrations (Chl) in the global ocean for Chl less than or equal to 0.25 milligrams per cubic meters (approximately 77% of the global ocean area). The algorithm is based on a color index (CI), defined as the difference between remote sensing reflectance (R(sub rs), sr(sup -1) in the green and a reference formed linearly between R(sub rs) in the blue and red. For low Chl waters, in situ data showed a tighter (and therefore better) relationship between CI and Chl than between traditional band-ratios and Chl, which was further validated using global data collected concurrently by ship-borne and SeaWiFS satellite instruments. Model simulations showed that for low Chl waters, compared with the band-ratio algorithm, the CI-based algorithm (CIA) was more tolerant to changes in chlorophyll-specific backscattering coefficient, and performed similarly for different relative contributions of non-phytoplankton absorption. Simulations using existing atmospheric correction approaches further demonstrated that the CIA was much less sensitive than band-ratio algorithms to various errors induced by instrument noise and imperfect atmospheric correction (including sun glint and whitecap corrections). Image and time-series analyses of SeaWiFS and MODIS/Aqua data also showed improved performance in terms of reduced image noise, more coherent spatial and temporal patterns, and consistency between the two sensors. The reduction in noise and other errors is particularly useful to improve the detection of various ocean features such as eddies. Preliminary tests over MERIS and CZCS data indicate that the new approach should be generally applicable to all existing and future ocean color instruments.

Hu, Chuanmin↗
NASA NTRS2014

Design Evolutuion of Hot Isotatic Press Cans for NTP Cermet Fuel Fabrication

Nuclear Thermal Propulsion (NTP) is under consideration for potential use in deep space exploration missions due to desirable performance properties such as a high specific impulse (> 850 seconds). Tungsten (W)-60vol%UO2 cermet fuel elements are under development, with efforts emphasizing fabrication, performance testing and process optimization to meet NTP service life requirements [1]. Fuel elements incorporate design features that provide redundant protection from crack initiation, crack propagation potentially resulting in hot hydrogen (H2) reduction of UO2 kernels. Fuel erosion and fission product retention barriers include W coated UO2 fuel kernels, W clad internal flow channels and fuel element external W clad resulting in a fully encapsulated fuel element design as shown.

Mireles, O. R.↗
NASA NTRS2014

Mitigating Thermal Runaway Risk in Lithium Ion Batteries

The JSC/NESC team has successfully demonstrated Thermal Runaway (TR) risk reduction in a lithium ion battery for human space flight by developing and implementing verifiable design features which interrupt energy transfer between adjacent electrochemical cells. Conventional lithium ion (li-Ion) batteries can fail catastrophically as a result of a single cell going into thermal runaway. Thermal runaway results when an internal component fails to separate electrode materials leading to localized heating and complete combustion of the lithium ion cell. Previously, the greatest control to minimize the probability of cell failure was individual cell screening. Combining thermal runaway propagation mitigation design features with a comprehensive screening program reduces both the probability, and the severity, of a single cell failure.

Darcy, Eric↗
NASA NTRS2018

Additive Manufacturing of Liquid Rocket Engine Combustion Devices: A Summary of Process Developments and Hot-Fire Testing Results

Additive Manufacturing (AM) is an emerging technology with a focus on complex metallic component fabrication: Enables complex shapes and internal features that were not possibly with traditional manufacturing techniques, and significant schedule and overall lifecycle cost reductions. To date at the NASA Marshall Space Flight Center (MSFC), combustion devices component hardware ranging in size from 100 - 35,000 lbf has been designed and manufactured using AM and many of these pieces have been hot-fire tested.

Gradl, Paul↗
NASA NTRSDate not supplied

Progress Towards the Design of a Natural Laminar Flow Wing for a Low-Boom Concept using CDISC

The X-59 is being developed to evaluate the ability to reduce sonic boom loudness to acceptable levels, with the ultimate goal of enabling supersonic flight overland. If successful, one of the future research challenges will be focused on reducing fuel burn. In this paper, Natural Laminar Flow (NLF) is proposed as a technology to decrease fuel burn for a low-boom configuration. This will require an evaluation of the compatibility of NLF wings for a low-boom configuration. As a first step towards this goal, the CATNLF method was employed using the CDISC design module to perform NLF design on an isolated wing from a low-boom configuration. The results show that the NLF wing features laminar flow over 46% of the wing upper surface, providing a potential 8.3 drag count reduction relative to the design with no laminar flow. Off-design analyses were additionally performed to evaluate the performance of the NLF wing for changes in angle of attack and Mach number. The results showed that the NLF wing offers a performance benefit over the entire range of off-design conditions considered, with most of the laminar flow maintained for near cruise conditions. Future work will consider the full configuration, which will enable an assessment of the impact of the NLF wing design on sonic boom loudness. Additionally, attachment line transition will be addressed, which was predicted to result in a loss of laminar flow on the inboard 50% span for this work. Finally, future research will focus on developing a method for effectively choosing the frequency-beta pairs used for the stability analysis to improve transition prediction and provide a more accurate estimate of the performance benefit.

Supersonic↗