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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

An Update on the Lithium-Ion Cell Low-Earth-Orbit Verification Test Program

A Lithium-Ion Cell Low-Earth-Orbit Verification Test Program is being conducted by NASA Glenn Research Center to assess the performance of lithium-ion (Li-ion) cells over a wide range of low-Earth-orbit (LEO) conditions. The data generated will be used to build an empirical model for Li-ion batteries. The goal of the modeling will be to develop a tool to predict the performance and cycle life of Li-ion batteries operating at a specified set of mission conditions. Using this tool, mission planners will be able to design operation points of the battery system while factoring in mission requirements and the expected life and performance of the batteries. Test conditions for the program were selected via a statistical design of experiments to span a range of feasible operational conditions for LEO aerospace applications. The variables under evaluation are temperature, depth-of-discharge (DOD), and end-of-charge voltage (EOCV). The baseline matrix was formed by generating combinations from a set of three values for each variable. Temperature values are 10 C, 20 C and 30 C. Depth-of-discharge values are 20%, 30% and 40%. EOCV values are 3.85 V, 3.95 V, and 4.05 V. Test conditions for individual cells may vary slightly from the baseline test matrix depending upon the cell manufacturer s recommended operating conditions. Cells from each vendor are being evaluated at each of ten sets of test conditions. Cells from four cell manufacturers are undergoing life cycle tests. Life cycling on the first sets of cells began in September 2004. These cells consist of Saft 40 ampere-hour (Ah) cells and Lith ion 30 Ah cells. These cells have achieved over 10,000 cycles each, equivalent to about 20 months in LEO. In the past year, the test program has expanded to include the evaluation of Mine Safety Appliances (MSA) 50 Ah cells and ABSL battery modules. The MSA cells will begin life cycling in October 2006. The ABSL battery modules consist of commercial Sony hard carbon 18650 lithium-ion cells configured in series and parallel combinations to create nominal 14.4 volt, 3 Ah packs (4s-2p). These modules have accumulated approximately 3000 cycles. Results on the performance of the cells and modules will be presented in this paper. The life prediction and performance model for Li-ion cells in LEO will be built by analyzing the data statistically and performing regression analysis. Cells are being cycled to failure so that differences in performance trends that occur at different stages in the life of the cell can be observed and accurately modeled. Cell testing is being performed at the Naval Surface Warfare Center in Crane, IN.

Reid, Concha M.↗
DOE OSTI2026

Iterative HOMER with uncertainties

We present iHOMER, an iterative version of the HOMER method to extract Lund fragmentation functions from experimental data. Through iterations, we address the information gap between latent and observable phase spaces and systematically remove bias. To quantify uncertainties on the inferred weights, we use a combination of Bayesian neural networks and uncertainty-aware regression. We find that the combination of iterations and uncertainty quantification produces well-calibrated weights that accurately reproduce the data distribution. A parametric closure test shows that the iteratively learned fragmentation function is compatible with the true fragmentation function.

Butter, Anja [Heidelberg Univ. (Germany); Sorbonne↗
NASA NTRS1982

Performance degradation and cleaning of photovoltaic arrays

NASA tests results from an 18 mo program of cleaning silicone-encapsulated and glass fronted solar cell panels in urban and desert environments to examine the effects of cleaning on module performance are reported. The panels were cleaned on weekly, monthly, quarterly, or semi-annual basis, while other panels of the same construction were not cleaned and served as controls. Commercially-available detergents and city water were employed for the tests, and the measurements were maintained of the modules' continuing short-circuit current output. The decay of the output was determined by least square regression analyses. Performance degradation was noticeably less in glass covered, rather than silicone-encapsulated modules which decayed faster in urban than in desert environments. Lower frequency cleanings are recommended where labor costs are high.

Sheskin, T. J.↗
NASA NTRS1989

Remote sensing of soils in the eastern Palouse region with Landsat Thematic Mapper

Soils of the Palouse region of eastern Washington State were investigated using Landsat Thematic Mapper (TM) band ratios to discriminate areas where erosion has caused paleosols to be exposed. Ratioed data were clustered and plotted to show soil lines which could be subdivided into various levels of organic matter and iron oxides. Successfully classified scenes of a summer fallow (bare soil) field were obtained with band ratios 1/4, 3/4, and 5/4 to map organic carbon and 3/4, 5/4, and 5/3 for the iron/carbon ratio indicator of erosion. Regression models were made with 5/4 data and organic carbon and 5/3 data and the iron/carbon ratio. Based on this analysis, 21 percent of the test field soils are exposed or nearly exposed paleosols.

Frazier, B. E.↗
NASA NTRS1990

Investigation of Air Transportation Technology at Ohio University, 1989-1990

The activities of the participants in the Joint University Program (JUP) at Ohio University are briefly surveyed. During 1989 to 1990, five topics received emphasis. A spectrum-efficient weather data uplink system was designed, constructed, and flight tested. An integrated Global Positioning System/Inertial Navigation System (GPS/INS) study continued, utilizing the Redundant strapdown Inertial Measurement Unit (IMU) on loan from NASA. The Ridge Regression theory was refined and applied to air navigation scenarios. System Identification theory was applied to GPS data to point the way to better understanding of the effects of Selective Availability on civilian users of this navigation system. An analysis of thought-related (electroencephalographic) signals for application to control of computer systems that could have significance in aiding paraplegics or for hands-off systems control in industrial or air traffic control areas was carried out.

Lilley, Robert W.↗
NASA NTRS2019

Mars Ascent Vehicle Hybrid Propulsion Development

Hybrid propulsion is being investigated as a propulsion method for a possible Mars Ascent Vehicle (MAV) application. MAV is part of a proposed larger Mars Sample Return (MSR) campaign plan to bring samples from Mars to earth for examination. The Mars Ascent Vehicle would launch Mars surface samples found and packaged by the Mars 2020 mission to orbit around Mars. This version of hybrid propulsion is based on a wax based solid fuel, called SP7A, and a Mixed Oxides of Nitrogen oxidizer, MON-25. SP7 is a new fuel formulation developed by Space Propulsion Group and was modified for this application to be resistant to Mars temperature extremes and modified again to lower the regression rate to become SP7A. MON-25 was chosen for its low freezing temperature. Due to cost constraints, MON-3 was the oxidizer used during testing through 2018. In 2019, full scale hybrid testing with MON-25 commenced in Mojave, CA by Whittinghill Aerospace. One flight motor will be subjected to thermal cycling in a vacuum and later fired in a vacuum to demonstrate the proposed Liquid Injection Thrust Vector Control system performance at White Sands Test Facility (WSTF). In addition, there will be MON-25 characterization work done at Purdue University and WSTF. Additional testing of subscale and full scale motors will be conducted with MON-3 with fuel grain stress, fuel grain support and case design test objectives by Space Propulsion Group Inc. of Butte, MT. This paper documents some of the testing, issues and accomplishments with the MAV hybrid propulsion option that is being considered (along with a two-stage solid propulsion option).

Story, G. T.↗
NASA NTRSDate not supplied

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of machine-learning (ML) models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a user-friendly app that has been created to deploy trained machine-learning (ML) models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of ML application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). The app gets user input for a turbofan design, preprocesses the input data, and deploys trained ML models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The ML predictive models were built by employing supervised deep-learning and K-nearest neighbor regression algorithms to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these ML models using the app shows that Aero-Engines AI is an easy-touse and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage. Current version of the app focuses on the performance prediction of conventional turbofans. However, the scope of the app can easily be expanded to include other engine types (such as turboshaft and hybrid-electric systems) after their ML models are developed. Overall, the use of a machine-learning app for aircraft engine concept assessment represents a promising area of development in aircraft engine conceptual design.

machine learning↗
NASA NTRS2023

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of machine-learning (ML) models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a user-friendly app that has been created to deploy trained machine-learning (ML) models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of ML application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). The app gets user input for a turbofan design, preprocesses the input data, and deploys trained ML models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The ML predictive models were built by employing supervised deep-learning and K-nearest neighbor regression algorithms to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these ML models using the app shows that Aero-Engines AI is an easy-touse and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage. Current version of the app focuses on the performance prediction of conventional turbofans. However, the scope of the app can easily be easily expanded to include other engine types (such as turboshaft and hybrid-electric systems) after their ML models are developed. Overall, the use of a machine-learning app for aircraft engine concept assessment represents a promising area of development in aircraft engine conceptual design.

machine learning↗
NASA NTRS2009

In-Situ Measurement of Hall Thruster Erosion Using a Fiber Optic Regression Probe

One potential life-limiting mechanism in a Hall thruster is the erosion of the ceramic material comprising the discharge channel. This is especially true for missions that require long thrusting periods and can be problematic for lifetime qualification, especially when attempting to qualify a thruster by analysis rather than a test lasting the full duration of the mission. In addition to lifetime, several analytical and numerical models include electrode erosion as a mechanism contributing to enhanced transport properties. However, there is still a great deal of dispute over the importance of erosion to transport in Hall thrusters. The capability to perform an in-situ measurement of discharge channel erosion is useful in addressing both the lifetime and transport concerns. An in-situ measurement would allow for real-time data regarding the erosion rates at different operating points, providing a quick method for empirically anchoring any analysis geared towards lifetime qualification. Erosion rate data over a thruster s operating envelope would also be useful in the modeling of the detailed physics inside the discharge chamber. There are many different sensors and techniques that have been employed to quantify discharge channel erosion in Hall thrusters. Snapshots of the wear pattern can be obtained at regular shutdown intervals using laser profilometry. Many non-intrusive techniques of varying complexity and sensitivity have been employed to detect the time-varying presence of erosion products in the thruster plume. These include the use quartz crystal microbalances, emission spectroscopy, laser induced flourescence, and cavity ring-down spectroscopy. While these techniques can provide a very accurate picture of the level of eroded material in the thruster plume, it is more difficult to use them to determine the location from which the material was eroded. Furthermore, none of the methods cited provide a true in-situ measure of erosion at the channel surface while the thruster is in operation (i.e. none yield a continuous channel erosion measurement). A recent fundamental sensor development effort has led to a novel regression, erosion, and ablation sensor technology (REAST). The REAST sensor allows for measurement of real-time surface erosion rates at a discrete surface location. The sensor was tested using a linear Hall thruster geometry (see Fig. 1), which served as a means of producing plasma erosion of a ceramic discharge chamber. The mass flow rate, discharge voltage, and applied magnetic field strength could be varied, allowing for erosion measurements over a broad thruster operating envelope. Results are presented demonstrating the ability of the REAST sensor to capture not only the insulator erosion rates but also changes in these rates as a function of the discharge parameters.

Polzin, Kurt↗
NASA NTRS2002

Power Measurement Errors on a Utility Aircraft

Extensive flight test data obtained from two recent performance tests of a UH 60A aircraft are reviewed. A power difference is calculated from the power balance equation and is used to examine power measurement errors. It is shown that the baseline measurement errors are highly non-Gaussian in their frequency distribution and are therefore influenced by additional, unquantified variables. Linear regression is used to examine the influence of other variables and it is shown that a substantial portion of the variance depends upon measurements of atmospheric parameters. Correcting for temperature dependence, although reducing the variance in the measurement errors, still leaves unquantified effects. Examination of the power difference over individual test runs indicates significant errors from drift, although it is unclear how these may be corrected. In an idealized case, where the drift is correctable, it is shown that the power measurement errors are significantly reduced and the error distribution is Gaussian. A new flight test program is recommended that will quantify the thermal environment for all torque measurements on the UH 60. Subsequently, the torque measurement systems will be recalibrated based on the measured thermal environment and a new power measurement assessment performed.

Bousman, William G.↗
NASA NTRS2012

CO2 Washout Testing of the REI and EM-ACES Space Suits

When a space suit is used during ground testing, adequate carbon dioxide (CO2) washout must be provided for the suited subject. Symptoms of acute CO2 exposure depend on partial pressure of CO2 (ppCO2), metabolic rate of the subject, and other factors. This test was done to characterize inspired oronasal ppCO2 in the Rear Entry I-Suit (REI) and the Enhanced Mobility Advanced Crew Escape Suit (EM-ACES) for a range of workloads and flow rates for which ground testing is nominally performed. Three subjects were tested in each suit. In all but one case, each subject performed the test twice. Suit pressure was maintained at 4.3 psid. Subjects wore the suit while resting, performing arm ergometry, and walking on a treadmill to generate metabolic workloads of about 500 to 3000 BTU/hr. Supply airflow was varied between 6, 5, and 4 actual cubic feet per minute (ACFM) at each workload. Subjects wore an oronasal mask with an open port in front of the mouth and were allowed to breathe freely. Oronasal ppCO2 was monitored in real time by gas analyzers with sampling tubes connected to the mask. Metabolic rate was calculated from the total CO2 production measured by an additional gas analyzer at the suit air outlet. Real-time metabolic rate was used to adjust the arm ergometer or treadmill workload to meet target metabolic rates. In both suits, inspired CO2 was affected mainly by the metabolic rate of the subject: increased metabolic rate significantly (P < 0.05) increased inspired ppCO2. Decreased air flow caused small increases in inspired ppCO2. The effect of flow was more evident at metabolic rates . 2000 BTU/hr. CO2 washout values of the EM-ACES were slightly but not significantly better than those of the REI suit. Regression equations were developed for each suit to predict the mean inspired ppCO2 as a function of metabolic rate and suit flow rate. This paper provides detailed descriptions of the test hardware, methodology, and results as well as implications for future ground testing in the REI-suit and EM-ACES.

Mitchell, Kathryn C.↗
DOE OSTI2024

Uniaxial compressive creep tests by spark plasma sintering of 70% theoretical density α -uranium and U-10Zr

Metallic fuels hold numerous advantages over conventional uranium dioxide fuels and are a key component of several liquid metal-cooled advanced reactor concepts including sodium fast reactors. These fuels undergo rapid swelling during early burnup; consequently, they spend most of their reactor lifetime in a porous state. The presence of this porosity alters many of the mechanical properties of the fuel including creep impacting fuel deformation during axial swelling. This work investigates the creep behavior of the porous fuel using a spark plasma sintering technique. Creep tests were performed for the first time on porous α-phase uranium and uranium with 10 wt. % zirconium (U-10Zr) samples. The samples of α-phase uranium and U-10Zr were fabricated from depleted uranium by spark plasma sintering and subjected to uniaxial compressive creep testing. Calculated stress exponents were found to be 2.6±1.6 and 5.7±1.4 for α-U and U-10Zr, respectively, and calculated activation energies were found to be 61.6±1.1kJ/mol for α-U. The creep data were also used to evaluate existing porosity inclusive in creep models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1980

Burning rate for steel-cased, pressed binderless HMX

The burning behavior of pressed binderless HMX laterally confined in 6.4 mm i.d. steel cases was measured over the pressure range 1.45 to 338 MPa in a constant pressure strand burner. The measured regression rates are compared to those reported previously for unconfined samples. It is shown that lateral confinement results in a several-fold decrease in the regression rate for the coarse particle size HMX above the transition to super fast regression. For class E samples, confinement shifts the transition to super fast regression from low pressure to high pressure. These results are interpreted in terms of the previously proposed progressive deconsolidation mechanism. Preliminary holographic photography and closed bomb tests are also described. Theoretical one dimensional modeling calculations were carried out to predict the expected flame height (particle burn out distance) as a function of particle size and pressure for binderless HMX burning by a progressive deconsolidation mechanism.

Fifer, R. A.↗
NASA NTRS1993

Computer assisted analysis of auroral images obtained from high altitude polar satellites

Automatic techniques that allow the extraction of physically significant parameters from auroral images were developed. This allows the processing of a much larger number of images than is currently possible with manual techniques. Our techniques were applied to diverse auroral image datasets. These results were made available to geophysicists at NASA and at universities in the form of a software system that performs the analysis. After some feedback from users, an upgraded system was transferred to NASA and to two universities. The feasibility of user-trained search and retrieval of large amounts of data using our automatically derived parameter indices was demonstrated. Techniques based on classification and regression trees (CART) were developed and applied to broaden the types of images to which the automated search and retrieval may be applied. Our techniques were tested with DE-1 auroral images.

Samadani, Ramin↗
NASA NTRS2003

Flight Investigation of Prescribed Simultaneous Independent Surface Excitations for Real-Time Parameter Identification

Near real-time stability and control derivative extraction is required to support flight demonstration of Intelligent Flight Control System (IFCS) concepts being developed by NASA, academia, and industry. Traditionally, flight maneuvers would be designed and flown to obtain stability and control derivative estimates using a postflight analysis technique. The goal of the IFCS concept is to be able to modify the control laws in real time for an aircraft that has been damaged in flight. In some IFCS implementations, real-time parameter identification (PID) of the stability and control derivatives of the damaged aircraft is necessary for successfully reconfiguring the control system. This report investigates the usefulness of Prescribed Simultaneous Independent Surface Excitations (PreSISE) to provide data for rapidly obtaining estimates of the stability and control derivatives. Flight test data were analyzed using both equation-error and output-error PID techniques. The equation-error PID technique is known as Fourier Transform Regression (FTR) and is a frequency-domain real-time implementation. Selected results were compared with a time-domain output-error technique. The real-time equation-error technique combined with the PreSISE maneuvers provided excellent derivative estimation in the longitudinal axis. However, the PreSISE maneuvers as presently defined were not adequate for accurate estimation of the lateral-directional derivatives.

Moes, Timothy R.↗
NASA NTRSDate not supplied

The INSTEP Monitoring Network: Merging High-and-Low Cost Measurements to Characterize California Wildfires

Despite challenges with data quality and scope, low-cost sensor networks have skyrocketed in popularity over the last 15 years, making air quality data available on refined spatial scales. More recently, studies have leveraged both high and low-quality instruments to create stronger “hybrid” models, with most studies focusing on particulate matter. Low-cost measurements typically represent ground-level emissions only, providing context for human health issues from climate change-driven events such as wildfires. Since low-cost sensors’ capabilities are localized, daily events and microclimates tend to dominate the data rather than larger regional or atmospheric trends. Likewise, their low cost explains their high uncertainty. In contrast, some regulatory-grade instruments produce column measurements as well, providing reliable information on a broader scope. To bridge this gap while expanding into gas-phase measurements, we deployed 12 air quality sensor packages in California, USA during the 2022 wildfire season. These INSTEP (Inexpensive Network Sensor Technology Exploring Pollution) monitors measure carbon monoxide (CO), carbon dioxide (CO2), ozone (O3), nitrogen dioxide (NO2), and several hydrocarbons including methane (CH4) and formaldehyde (HCHO). Half of the monitors were co-located with remote sensing spectrometers: NASA Pandora and Total Column Carbon Observing Network (TCCON). The overlap in pollutants includes NO2, O3, and HCHO between the INSTEP monitors and the Pandora column measurements. TCCON covers column CO, CO2, and CH4, rounding out our comparison. Most of the monitors were distributed throughout the San Francisco Bay area, and an additional three were located within 100 km of Los Angeles. The sites ranged in geographic and population characteristics, including desert, mountainous, coastal, and urban locations. Since varying environmental conditions such as temperature and pressure are known to challenge sensor performance, we will apply newer sensor “calibration” techniques meant to combat this. We will normalize our sensor signals by z-scoring them prior to applying a single calibration model in the form of multivariate linear regression or an artificial neural network. While this technique has been validated for the hydrocarbon and ozone sensor types (metal oxide), it has not yet been tested on electrochemical and non-dispersive infrared sensors, which are also used in the INSTEP monitors. This will serve as a test to see if this normalization technique – or another – is most effective in accounting for environmental differences among sensors. Related data analysis efforts have found success with a variety of geospatial analysis techniques, including weighted network models in which high-quality instruments are given higher weights than their low-cost counterparts. Our preliminary analysis will focus on kriging, which uses a Gaussian algorithm to assign weights, providing estimated pollution levels at locations between monitors. Smoke trajectory and evolution will also be considered using both measurement types. We also aim to baseline subtract our emission estimates from each region to determine which portion of emissions are regional and local, further characterizing burn differences in northern and southern California fires. Future directions include using INSTEP jointly with TEMPO satellite data, and mobile deployments on aircraft and uncrewed aerial vehicles (UAV).

Low-cost sensors↗
NASA NTRS2011

CO2 Washout Testing of the REI and EM-ACES Space Suits

Requirements for using a space suit during ground testing include providing adequate carbon dioxide (CO2) washout for the suited subject. Acute CO2 exposure can lead to symptoms including headache, dyspnea, lethargy and eventually unconsciousness or even death. Symptoms depend on several factors including partial pressure of CO2 (ppCO2), duration of exposure, metabolic rate of the subject and physiological differences between subjects. The objective of this test was to characterize inspired oronasal ppCO2 in the Rear Entry I-Suit (REI) and the Enhanced Mobility Advanced Crew Escape Suit (EM-ACES) across a range of workloads and flow rates for which ground testing is nominally performed. Three subjects were tested in each suit. In all but one case, each subject performed the test twice to allow for comparison between tests. Suit pressure was maintained at 4.3 psid. Subjects wore the suit while resting, performing arm ergometry, and walking on a treadmill to generate metabolic workloads of approximately 500 to 3000 BTU/hr. Supply airflow was varied at 6, 5 and 4 actual cubic feet per minute (ACFM) at each workload. Subjects wore an oronasal mask with an open port in front of the mouth and were allowed to breathe freely. Oronasal ppCO2 was monitored real-time via gas analyzers with sampling tubes connected to the oronasal mask. Metabolic rate was calculated from the total CO2 production measured by an additional gas analyzer at the air outlet from the suit. Real-time metabolic rate was used to adjust the arm ergometer or treadmill workload to meet target metabolic rates. In both suits, inspired CO2 was primarily affected by the metabolic rate of the subject, with increased metabolic rate resulting in increased inspired ppCO2. Suit flow rate also affected inspired ppCO2, with decreased flow causing small increases in inspired ppCO2. The effect of flow was more evident at metabolic rates greater than or equal to 2000 BTU/hr. Results were consistent between suits, with the EM-ACES demonstrating slightly better CO2 washout than the REI suit, but not statistically significant. Regression equations were developed for each suit to predict the mean inspired ppCO2 as a function of metabolic rate and suit flow rate. This paper provides detailed descriptions of the test hardware, methodology and results, as well as implications for future ground testing in the REI and EM-ACES.

Mitchell, Kate↗
NASA NTRS2019

Sound Quality Metric Indicators of Rotorcraft Noise Annoyance Using Multilevel Regression Analysis

Although every helicopter in operation has to go through a noise certification process, annoyance due to helicopters still persists within various communities. This implies that certification metrics do not capture the full range of human response and that predicted reactions could be supplemented with other information, which could be acoustic or non-acoustic in nature. The rotorcraft sound quality metric (RoQM) psychoacoustic experiment was designed to determine the relative importance of sound quality metrics (SQMs), such as sharpness, tonality, loudness, fluctuation strength and impulsiveness, on human annoyance to rotorcraft sounds. Starting from a baseline helicopter recording, SQMs were varied synthetically and presented to subjects who responded with an annoyance rating. The RoQM test took place in 2017 at the NASA Langley Research Center in the Exterior Effects Room. A total of 105 sounds were played to 40 subjects. The relationship between helicopter noise sound quality and annoyance is modeled using multilevel regression in this work, which takes into account the variability of responses across subjects. Previous analyses did not consider such a grouping of the data.

Matthew Boucher↗