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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Experiments on Exhaust Noise of Tightly Integrated Propulsion Systems

A wide-ranging series of tests have been completed that seek to map the effects of installation, including jet by jet interaction effects, on exhaust noise from various nozzles in forward flight. The primary data was far-field acoustic spectral directivity. The goals of the test series were (i) to generate enough data for empirical models of the different effects, and (ii) to provide data for advanced computational noise predictions methods applied to simplified yet realistic configurations. Data is presented that demonstrate several checks on data quality and that provide an overview of trends observed to date. Among the findings presented here: (i) Data was repeatable between jet rigs for single nozzles with and without surfaces to within +/- 0.5 dB. (ii) The presence of a second jet caused a strong reduction of the summed noise in the plane of the two plumes and an increase over the expected source doubling in most other azimuthal planes. (iii) The impact of the second jet was reduced when the jets were unheated. (iv) The impact of adding a second isolated rectangular jet was relatively independent of the nozzle aspect ratio up to aspect ratio 8:1. (v) Forward flight had similar impact on a high aspect ratio (8:1) jet as on an axisymmetric jet, except at the peak noise angle where the impact was less. (vi) The effect of adding a second round jet to a tightly integrated nozzle where the nozzle lip was less than a diameter from the surface was very dependent upon the length of the surface downstream of the nozzle. (vii) When the nozzles were rectangular and tightly integrated with the airframe surface the impact of a second jet was very dependent upon how close together the two jets were. This paper serves as an overview of the test; other papers presented in the same conference will give more detailed analysis of the results.

Noise↗
NASA NTRSDate not supplied

Evaluation of Silicon Carbide Pressure Sensor in Turbofan Engine Core Exhaust Nozzle

We report the results of the evaluation of single crystal 4H-silicon carbide piezoresistive pressure sensors that were directly inserted at the compressor and core exhaust nozzle exits, in shear contact with the engine-internal flow streams of the NASA DGEN Aeropropulsion Research Turbofan, where the operating temperatures at maximum power were ~230 oC, and ~460 oC, respectively. In addition to demonstrating sensor survivability during this maiden test, the frequency responses of the silicon-carbide sensors at the core-nozzle exit were compared against industry-standard silicon-based piezoresistive pressure transducers that externally placed, using an infinite-tube-probe arrangement. The low-voltage output of these early-development SiC sensors limited the frequency range with an acceptable signal-to-noise-ratio for the current application to less than about 2,500 Hz. The low output of the SiC sensors were due to a conservative burst-pressure diaphragm design that can be optimized to increase the frequency range. The results from this initial campaign offered insights to aspects of the sensor that would require further improvement, with the goal of achieving full-bandwidth capture of engine unsteady pressure fluctuations by direct interrogation of the flow field in hostile-environment engine-core components.

Silicon Carbide↗
NASA NTRSDate not supplied

Evaluation of SiC Pressure Sensors in Turbofan Engine Core Exhaust Nozzle

We report the results of the evaluation of single crystal 4H-silicon carbide piezoresistive pressure sensors that were directly inserted at the compressor and core exhaust nozzle exits, in shear contact with the engine-internal flow streams of the NASA DGEN Aeropropulsion Research Turbofan, where the operating temperatures at maximum power were ~230°C, and ~460°C, respectively. In addition to demonstrating sensor survivability during this maiden test, the frequency responses of the silicon-carbide sensors at the core-nozzle exit were compared against industry-standard silicon-based piezoresistive pressure transducers that externally placed, using an infinite-tube-probe arrangement. The low-voltage output of these early-development SiC sensors limited the frequency range with an acceptable signal-to-noise-ratio for the current application to less than about 2,500 Hz. The low output of the SiC sensors were due to a conservative burst-pressure diaphragm design that can be optimized to increase the frequency range. The results from this initial campaign offered insights to aspects of the sensor that would require further improvement, with the goal of achieving full-bandwidth capture of engine unsteady pressure fluctuations by direct interrogation of the flow field in hostile-environment engine-core components.

Silicon Carbide↗
DOE OSTI2020

DIGITAL APPLICATIONS USING REAL-TIME VEHICLE EXHAUST INFORMATION

Vehicle emission is a major source of air pollution that causes a significant number of deaths globally. It has a profound impact on energy and the environment as well. The existing vehicle emission monitoring system is unable to help mitigating the pollution properly and therefore, requires precise real-time pollution measurement. The purpose of this paper is to discuss novel applications using the real-time measurement of pollutants from a vehicle tailpipe where exhaust gases enter the environment. Today, it is possible to measure such emission due to the emergence of affordable digital technologies such as the Internet of Things (IoT), wireless connectivity, cloud platform, and artificial intelligence. This paper discusses how digital technologies can be used for real-time monitoring of NOx gas as a measure of vehicle emission and predictive analytics applications. A description of data collection and pre-processing methodologies, actual collected data, and an approach to identify patterns between inputs such as vehicle speed and altitude and output such as NOx emission are included. Applying a simple neural network has produced promising results and is a first step towards developing predictive applications.

Digital, Vehicle Exhaust, IoT, AI, 1.4.2, Predicti↗