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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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100 records · Page 6
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NASA NTRSDate not supplied

Quantifying Uncertainty of Landing and Takeoff Noise for Commercial Supersonic Aircraft

Of the many challenges faced by manufacturers attempting to offer supersonic travel to the public, the uncertainty in predicting the noise of these aircraft in airport operations has an immediate impact. No noise regulation exists in FAA or ICAO for certifying such aircraft, as these organization require solid data, usually from existing aircraft. Manufacturers are taking large risks to design a vehicle not knowing whether it will be allowed to fly. A partial solution to this conundrum is to use physics-based simulations to provide the “data” used to calibrate system-level prediction methods, carefully documenting the uncertainty of the method for application to supersonic aircraft. A close look at the accuracy of empirical prediction methods points to areas where improvements need to be made if noise studies of supersonic aircraft are to be useful. As NASA embarks on a focused research program to improve predictions of noise from the noise-dominant propulsion noise of commercial supersonic aircraft, this paper documents the work done to baseline the uncertainties found in today’s noise prediction methods. A relatively simplistic method was developed, summarizing the error of the empirical methods on a component basis and following their impact on the total aircraft during landing and takeoff operations using Monte Carlo analysis. By this method it is found that current empirical noise prediction methods have an uncertainty of 1.5 EPNdB cumulative for propulsion noise of a representative conventional subsonic passenger aircraft. When applied to likely near-term supersonic commercial aircraft, the uncertainty is 7.6 EPNdB cumulative, a difference that must be reduced if the prediction methods are to guide decision makers.

Airport noise↗
NASA NTRS2022

Greenhouse Gas Emission Estimations for 2016-2020 using the Sherlock Air Traffic Data Warehouse

Data and analyses are presented on the utilization of aircraft in the U.S. and the greenhouse gas emissions that they create. Commercial passenger and cargo aviation flight data, captured in the Sherlock data warehouse at NASA Ames over the five years from 2016 to 2020, is used to estimate the miles flown by major aircraft models. The estimates for aggregate annual number of flights are validated against data published by the Bureau of Transportation Statistics. The corresponding fuel usage is estimated using the International Civilian Aviation Organization (ICAO) fuel use tables and carbon dioxide emissions are calculated using a fuel-use multiplicative factor. A key conclusion of this analysis is that a small number of long-haul flights (with ranges greater than 2485 statute miles) create a disproportionately large fraction (30%) of annual total U.S. aviation-related carbon dioxide emissions, while a relatively large number of short flights (less than 311 statute miles) contribute a small net amount (less than 5%) of U.S. aviation-related carbon dioxide emissions. These U.S. results are consistent with a similar recent 2020 emissions study conducted by EUROCONTROL.

Emissions↗
NASA NTRSDate not supplied

Wake Vortex Effects Between Urban Air Mobility Aircraft

This study models the wake-induced downwash of an Urban Air Mobility (UAM) aircraft and the wake’s effects on a trailing aircraft’s dynamic stability when intersecting the wake trail. The Proctor wake vortex model is used to compute the wake-induced downwash over a 0.8 × 0.8 nautical mile flight area. The model is complemented by core radius growth, Proctor single phase wake decay, wake propagation, and Lamb wake aging. The wake data is then stored and loaded to the trailing aircraft as an atmospheric condition to affect the dynamics. Preliminary simulations include modeling the downwash from multiple UAM aircraft over the flight area and determining the normalized wake reduction at the ICAO 5 nautical mile separation criteria for a LIGHT aircraft trailing a MEDIUM aircraft.

Wake Vortex↗
NASA NTRSDate not supplied

Particle and Trace Gas Emissions Indices Measured During the 2021 Boeing ecoDemonstrator Emissions Ground Test

We present particle and trace gas emissions indices sampled on the ground at 30 meters behind the CFM LEAP-1B engines of the 2021 Boeing ecoDemonstrator, an Alaska Airlines 737-9 aircraft. Testing was carried out at Boeing Field in Seattle, WA, USA in Fall of 2021. Four different fuels were investigated including a 100% sustainable aviation fuel (SAF), a petroleum-based Jet A fuel, and two SAF blends. Total and non-volatile particle number concentrations were measured with a pair of condensation particle counters with one operating behind a custom-built thermal denuder heated to 350 degrees Celsius. Similarly, total and non-volatile particle number size distributions were measured with a pair of Scanning Mobility Particle Sizers (SMPSs). Non-volatile particle mass was estimated from particle light absorption techniques using an assumed mass absorption coefficient, while particle chemical speciation was measured by an Soot Particle Aerosol Mass Spectrometer (SP-AMS). A detailed list of instruments is given on the project website [1]. Overall, the results are consistent with expectations based on ICAO Emissions Databank certification data for the LEAP-1B with a stark reduction in non-volatile particle number and mass observed for the higher thrust conditions when the combustor was staged. The production of volatile particles under these conditions as well as experimental considerations related to background subtraction methods will be discussed. References: [1] Boeing ecoDemonstrator Science and Engineering Team (2022). 2021 Boeing ecoDemonstrator Emissions Ground Test Dataset

Richard H Moore↗
NASA NTRSDate not supplied

Transient Aircraft Soot Emissions Indicate That Steady-State Measurements Likely Underestimate Real-World, Take-Off Emissions: Time-Varying Aircraft Take-Off Emissions Indices Measured at Los Angeles International Airport

Aircraft engine emissions are unique among mobile pollution sources in that their impacts affect the local air quality near airports as well as upper tropospheric composition and climate over regional-to-hemispheric scales. Furthermore, air travel and its resulting emissions are expected to rebound from the recent COVID-related lows to increase dramatically over the next several decades. Given the multi-decade service lifetime of many commercial aircraft, it is critically important to quantitatively understand the real-world emissions coming from these engines in order to inform environmental assessment and modelling activities. Here, we present a detailed analysis of aircraft emissions during take-off operations at Los Angeles International Airport. The data were collected as part of the NASA Alternative Fuel Effects on Contrails and Cruise Emissions (ACCESS) project in May 2014, and the dataset is publicly available as described by Moore et al. [1]. In particular, we focus on the time-varying nature of the plume concentrations where clear differences in particle size and non-volatile particle fraction are observed during the early portion of the take-off plume relative to the later portion of the plume. We compare the transient emissions indices measured here to engine certification values in the International Civil Aviation Organization (ICAO) Emissions Databank, which suggests that steady-state measurements may underestimate the real-world, non-volatile particle emissions. The implications of this finding for modelling aircraft particle emissions will be discussed.

Richard H. Moore↗
NASA NTRSDate not supplied

Particle and Trace Gas Emissions Indices Measured During the 2021 Boeing ecoDemonstrator Emissions Ground Test

We present particle and trace gas emissions indices sampled on the ground at 30 meters behind the CFM LEAP-1B engines of the Boeing ecoDemonstrator 737-9 aircraft. Testing was carried out at Boeing Field in Seattle, WA, USA in Fall of 2021. Four different fuels were investigated including a 100% sustainable aviation fuel (SAF), a petroleum-based Jet A fuel, and two SAF blends. Total and non-volatile particle number concentrations were measured with a pair of condensation particle counters with one operating behind a custom-built thermal denuder heated to 350 degrees Celsius. Similarly, total and non-volatile particle number size distributions were measured with a pair of Scanning Mobility Particle Sizers (SMPSs). Non-volatile particle mass was estimated from particle light absorption techniques using an assumed mass absorption coefficient, while particle chemical speciation was measured by an Soot Particle Aerosol Mass Spectrometer (SP-AMS). A detailed list of instruments is given on the project website [1]. Overall, the results are consistent with expectations based on ICAO Emissions Databank certification data for the LEAP-1B with a stark reduction in non-volatile particle number and mass observed for the higher thrust conditions when the combustor was staged. The production of volatile particles under these conditions as well as experimental considerations related to background subtraction methods will be discussed.

Benjamin A. Nault↗
NASA NTRSDate not supplied

Global Variability in Sonic Boom Exposure due to Macroscopic Effects

Supersonic flight over land has been prohibited since 1973 due to the loudness of sonic booms. NASA is building the X-59 aircraft as part of its Quesst mission to demonstrate low-loudness shaped sonic booms, or “sonic thumps.” The Quesst mission will gather human perception data via a series of community noise surveys across the USA. The noise dose and perceptual response data will be provided to the International Civil Aviation Organization (ICAO) and the Federal Aviation Administration for use in determining potential future supersonic aircraft noise certification standards, effectively changing the prohibition from a speed limit to a noise limit. These noise regulations must be globally effective, as long travel distances see the largest benefit to supersonic flight. The state of the atmosphere through which a sonic boom travels affects the size of the region exposed to sound, the “carpet width” (CW), as well as the loudness. The focus of this dissertation is to understand and quantify the expected loudness and CW of sonic booms due to the macroscopic atmospheric effects around the world. A pair of large-scale propagation simulation studies were conducted using the NASA PCBoom code to compare predicted sonic boom loudness and CW statistics first across the USA and then across the world. For the USA study, near-field data of the X-59 in steady cruise was propagated at 4 cardinal headings at 138 locations through 5 years of Climate Forecast System Version 2 (CFSv2) atmospheric profiles. Results of a bootstrap forest predictor screening model indicated the importance of climate zone, latitude, ground elevation, season, and heading. It also noted the unimportance of time of day for predicting loudness and CW. The data is visualized in aggregate, and then broken out geographically, by season and heading, and by climate zone. Multiple linear regression models were fit to the data from the 138 locations so that estimates of the loudness and CW can be produced anywhere in the US. The results can aid in planning when and where to fly the X-59. For the global study, near-field data from three aircraft, the X-59 in a quiet and loud configuration, B-58, and Concorde, were propagated at four cardinal headings through data from three atmospheric models, the CFSv2, the Global Forecast System (GFS), and the ECMWF Reanalysis Version 5 (ERA5), at 100 global locations over 1 year. Results of a bootstrap forest predictor screening model indicated the importance of climate zone, ground elevation, season, and heading. Similar to the US study, the model indicated time of day was not an important predictor. The model also indicated that choice of weather model was not important, so the atmospheric model data are effectively interchangeable. The ERA5 model was chosen for use in an extension of the study to include 18 additional locations to ensure sampling of every climate zone. Loudness and CW results are shown in aggregate, and split geographically and by heading, season, and climate. Multiple linear regression models were fit to the data from the 118 locations so that estimates of loudness and CW can be produced around the world. N-waves and shaped booms did not have the same global variability. Koppen-Geiger climate zones were used as the climate zone definition for the global study. These are available as present-day and future climate projections. Making use of the multiple linear regression models, the future climate zones were input to estimate the effect of the changing climate on sonic boom loudness and CW. Results indicate that a changing climate would have little impact on the effectiveness of noise regulations.

X-59↗
NASA NTRSDate not supplied

Energy and Aviation

Explore the source record for details and available documents.

Aeronautics↗
NASA NTRSDate not supplied

Exercising Prediction Validation Methods for Analysis of Quiet Supersonic Overflight

En route noise certification procedures for quiet supersonic aircraft are in development under the International Civil Aviation Organization for a proposed standard that could enable civil supersonic overland flight. While these quiet supersonic aircraft do not exist yet, methods are being developed and evaluated using existing N-wave empirical datasets and low-boom simulation datasets. One potential aspect of future certification methods is the ability to use a validated prediction model to predict the certification noise level under reference day weather conditions. Methods to validate predictions, such as the two-sample t-test, Fisher’s combined probability test, two-sample Kolmogorov-Smirnov test, and equivalence testing, have been exercised and modified for this application. While some methods compare mean values, others compare values across the distribution, and a combination of methods can be used. The methods were applied to a subset of an N-wave dataset to demonstrate the applicability and identify potential areas for improvement. Atmospheric turbulence variability was included as a factor in these analyses through KZKFourier propagation simulations with parameters matching actual flights and weather conditions. Results are presented for six noise metrics (PL, ASEL, BSEL, DSEL, ESEL, and ISBAP), and plans to expand the analyses are discussed.

sonic boom↗