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At least 19 records
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NASA NTRS2020

Independent Analyses of Galveston QSF18 Social Survey

A set of independent analyses was performed of the findings of NASA’s QSF18 data collection exercise in Galveston, TX. These analyses included development of regression-based and other dosage-response relationships between the prevalence of annoyance with low-amplitude sonic booms and Perceived Level measures of single event and cumulative exposure. They also included detailed analyses of the effects of panelist attrition; of participation reminder messages sent to panelists; the ability to determine panelist locations at the time of exposure; and the effects of rattle and vibration on annoyance judgments, among other topics. The report summarizes the implications of its findings for the design of studies of community response to carpet booms created during future deployments of NASA’s X-59 aircraft, and recommends several design measures to improve the efficiency of data collection.

sonic boom↗
NASA NTRS2020

Quiet Supersonic Flights 2018 (QSF18) Test: Galveston, Texas Risk Reduction for Future Community Testing with a Low-Boom Flight Demonstration Vehicle

The Quiet Supersonic Flights 2018 (QSF18) Program was designed to develop tools and methods for demonstration of overland supersonic flight with an acceptable sonic boom, and collect a large dataset of responses from a representative sample of the population. Phase 1 provided the basis for a low amplitude sonic boom testing in six different climate regions that will enable international regulatory agencies to draft a noise-based standard for certifying civilian supersonic overland flight. Phase 2 successfully executed a large scale test in Galveston, Texas, developed well documented data sets, calculated dose response relationships, yielded lessons, and identified future risk reduction activities.

Galveston↗
NASA NTRS2020

Quiet Supersonic Flights 2018 (QSF18) Test: Galveston, Texas Risk Reduction for Future Community Testing with a Low-Boom Flight Demonstration Vehicle

The Quiet Supersonic Flights 2018 (QSF18) Program was designed to develop tools and methods for demonstration of overland supersonic flight with an acceptable sonic boom, and collect a large dataset of responses from a representative sample of the population. Phase 1 provided the basis for a low amplitude sonic boom testing in six different climate regions that will enable international regulatory agencies to draft a noise-based standard for certifying civilian supersonic overland flight. Phase 2 successfully executed a large scale test in Galveston, Texas, developed well documented data sets, calculated dose response relationships, yielded lessons, and identified future risk reduction activities.

Galveston↗
NASA NTRS2024

QSF18 Nonresponse Follow-up Reminders Survey Data Supplemental File

This minimal data set contains anonymized study subject identifier (PARTICIPANT_ID) and non-response follow up type (group) from the single events surveys conducted during the Quiet Supersonic Flights 2018 risk reduction study in Galveston, Texas, in November 2018. Nonresponse follow up groups and procedures are defined and discussed in Page et al. 2020, Section 6.2 (NASA/CR-2020-220589/Volume I). The data cleaning conventions are consistent with the assumptions of Lee et al. in the treatment of the single events survey data (Lee, Rathsam, Wilson (2020). Journal of the Acoustical Society of America. 147, doi: 10.1121/10.0001021). Filename: reminder_groups.csv Dimensions: 371 rows by 2 columns. Variables: PARTICIPANT_ID, group PARTICPANT_ID: numeric (integer, six digits) group: character string taking one of four values ('Email - No Reminder'; 'Email - Reminder'; 'Text - No Reminder'; 'Text - Reminder').

sample survey↗
NASA NTRS2021

Simulations and case study of X-59 low-booms propagated through measured atmospheric profiles

NASA's X-59 Quiet Supersonic Technology aircraft will soon be used to collect data to support the development of a dose-response relationship between low-boom level and human perception. The X-59's low-boom level will depend on aircraft conditions and trajectory, which can be controlled, and on atmospheric conditions, which cannot be controlled. To assess variability in low-boom levels produced by realistic atmospheres, NASA's PCBoom code was used to simulate propagation of an X-59 nearfield pressure condition through atmospheric profiles measured during NASA's Quiet Supersonic Flights 2018 (QSF18) test. Despite QSF18 lasting only 11 days, substantial weather variability occurred including snow and record high temperatures. A PL range of about 8.5 dB was predicted due to the QSF18 atmospheric variability. These results demonstrate the necessity for X-59's flight condition to be adjusted based on atmospheric conditions in order to achieve desired loudness levels during community surveys. Undertrack booms' Perceived Levels (PL) were predicted not to exceed 75 dB, X-59's target level in a standard atmosphere. Attenuation rate, ray tube area, path length, and other quantities are presented throughout propagation for the atmospheres that produce the loudest and quietest booms. Humidity differences below 15kft were a primary driver of the PL differences.

X-59↗
NASA NTRS2023

Multilevel Logistic Regression with Random Slope for Community Annoyance Survey Data

This paper documents recent dose-response modeling work at NASA in anticipation of follow-on work by a contactor. Specifically, this paper compares the results of a Bayesian MLR model with a fixed slope to one with a random slope using WSPR and QSF18 data. Previously reported dose-response modeling efforts of WSPR and QSF18 data have used a MLR model with a fixed slope term. A random slope may more accurately depict the dose-response relationship of individuals in the efforts to produce a population summary dose-response curve. Results of a fixed versus random slope model with WSPR and QSF18 data indicate minimal difference between the modeling methods. The simpler fixed slope model is preferable for these data, but these results do not preclude consideration of a random slope term in modeling efforts of future X-59 community test data.

dose-response↗
NASA NTRSDate not supplied

Simulations of X-59 Low-Booms Propagated Through Measured Atmospheric Profiles in Galveston, Texas

During NASA’s Quiet Supersonic Flights 2018 (QSF18) test, residents of Galveston, Texas and surrounding communities were exposed to low amplitude sonic booms for a community noise survey. Despite the flight test lasting only 11 days, substantial weather variability occurred including snow and record high temperatures. Similar atmospheric variability could occur in future community noise flight tests with the X-59 Quiet Supersonic Technology aircraft that is currently being constructed. X-59 is designed to have a Stevens Mark VII Perceived Level (PL) of 75 dB in a standard atmosphere. In this work, X-59’s low-boom performance in real atmospheres was tested by using NASA’s PCBoom code to simulate propagation of its nearfield pressure through the atmospheric profiles measured during QSF18. Results indicate undertrack booms would not exceed 75 PLdB in these atmospheres. A range of about 8.5 PLdB between the loudest and quietest undertrack boom was observed indicating adjustments to the X-59 flight condition may be needed to achieve target loudness levels during future sonic boom community noise surveys. Attenuation rate, ray tube area, path length and other quantities throughout propagation of the loudest and quietest booms are presented, which indicate humidity differences below 15kft were a primary driver of the PL differences.

sonic boom↗
NASA NTRS2022

Comparison of Likelihood Methods for Generalized Linear Mixed Models with Application to Quiet Supersonic Flights 2018 Data

Repeated measurement will be a feature of the survey data collected during the Quesst missionX-59 community response tests (CRT). Since each participant will report his or her categorical level of annoyance in response to multiple events, the responses from any single individual may be correlated with one another. Several models within the class of generalized linear mixed models (GLMM) are pertinent to the analysis of correlated categorical outcomes; the random intercept logistic regression model is one example. Both Bayesian and frequentist methods for fitting these models are available, with frequentist methods relying on some form of approximation (of either an integral or the integrand) that appears in the marginal likelihood function. Given several anticipated similarities of the X-59 CRT data to data collected during a past risk reduction, Quiet Supersonic Flights 2018 (QSF18), this short note is intended to create awareness. It documents an instance in which a reported population average dose-response relationship derived from QSF18 single event data was distorted by the integral approximation applied in likelihood-based methods. We review some of the available literature on the topic, compare the outputs of several different computational approaches implemented in available statistical software, and present simple corrective actions that may be useful during the Quesst mission.

dose-response model↗
NASA NTRS2022

Consistency of Annoyance Perception of Sonic Booms and Survey Satisficing

There is a potential in community sonic boom tests for survey measurement error due to recall errors. This occurs when a reported value differs from a participant’s true experience. The two topics examined in this paper are 1) recall bias: how consistently participants recall their annoyance to sonic thump events and 2) survey satisficing: whether participants opt for early survey termination if the option is available. Data from QSF18 were examined for evidence of recall bias and survey satisficing via inconsistencies between single event and daily summary survey reports. In terms of recall bias, when only one single event survey and daily summary survey were submitted by a participant on a particular day, both the single event and daily summary annoyance ratings match in the majority of instances (167 of 186). In terms of survey satisficing, there were fewer questions in the daily summary survey if the participant reported not hearing any sonic thumps during the day. Nevertheless, the instances of participants inconsistently reporting boom audibility between the single event and daily summary survey are relatively few (66 of 767). Therefore, the results of this study provide evidence to rule out recall bias and satisficing as sources of error in the QSF18 study.

Recall bias↗
NASA NTRSDate not supplied

Dose Error Impacts on A Collection of Realistic Dose-Response Curves Based on A NASA Sonic Boom Community Noise Survey

The National Aeronautics and Space Administration (NASA) plans to conduct surveys of community response to quiet supersonic flight to collect dose-response data for international regulators. Previous models of noise dose versus annoyance response ignored uncertainty in the noise dose experienced by survey respondents. This dose error causes attenuation bias and results in inaccurate dose-response relationships. The impacts of dose errors can be explored by introducing error into the dose estimates of a simulated community noise survey. The simulated population annoyance response is determined by specific noise response characteristics, including the onset of annoyance intercept, rate of increasing annoyance, participant intercept variability, and response rates. This paper explores the effects of dose errors on notional populations created by perturbing the noise response characteristics observed in participants in a recent NASA flight test, QSF18. The QSF18-based population parameters were shifted up to ±20% to create the study populations. For the anticipated dose range of the X-59, changes to the onset of annoyance intercept have the greatest impact on erroneous model results. Quantifying point estimate errors illustrates the impact of dose error, with errors up to 14 dB observed for a fixed high annoyance percentage.

dose-response modeling↗
NASA NTRSDate not supplied

Dose Error Impacts on A Collection of Realistic Dose-Response Curves Based on A NASA Sonic Boom Community Noise Survey

The National Aeronautics and Space Administration (NASA) plans to conduct surveys of community response to quiet supersonic flight to collect dose-response data for international regulators. Previous models of noise dose versus annoyance response ignored uncertainty in the noise dose experienced by survey respondents. This dose error causes attenuation bias and results in inaccurate dose-response relationships. The impacts of dose errors can be explored by introducing error into the dose estimates of a simulated community noise survey. The simulated population annoyance response is determined by specific noise response characteristics, including the onset of annoyance intercept, rate of increasing annoyance, participant intercept variability, and response rates. This paper explores the effects of dose errors on notional populations created by perturbing the noise response characteristics observed in participants in a recent NASA flight test, QSF18. The QSF18-based population parameters were shifted up to ±20% to create the study populations. For the anticipated dose range of the X-59, changes to the onset of annoyance intercept have the greatest impact on erroneous model results. Quantifying point estimate errors illustrates the impact of dose error, with errors up to 14 dB observed for a fixed high annoyance percentage.

dose-response modeling↗
NASA NTRS2020

Development of a Weather-Robust Ground-Based System for Sonic Boom Measurements

This report describes Brigham Young University’s (BYU) development and testing of a weather-robust, ground-based system for sonic boom measurements, carried out in support of NASA’s Quiet Supersonic Flight (QSF) initiative. The microphone configuration system, referred to as the Compact Outdoor Unit for Ground-based Acoustical Recordings (COUGAR, for the BYU mascot), was tested at NASA’s 2018 Quiet Supersonic Flight (QSF18) campaign and at the subsequent 2019 Carpet Determination in Entirety Measurements (CarpetDIEM) program.

sonic boom↗
NASA NTRS2022

An Adaptation of ISO 11204 using Customized Correction Grades to Mitigate Ambient Noise Effects when Computing Sonic Boom Loudness Levels

A spectral-based correction adapted from ISO 11204 [1] is investigated here to mitigate the effects of ambient noise contamination of sonic booms recorded by noise monitors during field tests. The algorithm from sections 5.4.2 and 7 of ISO 11204 is customized using six nonstandard correction grades in addition to implementing the two standardized grades described in ISO 11204. The six nonstandard grades allow for more aggressive correction of the levels of the sonic boom spectrum when they are proximate to the ambient spectrum. Of the eight correction grades, the most aggressive custom correction grade, termed “Custom F” here, performed best under the conditions that were studied. Consequently, “Custom F” is recommended for use when processing in-field recordings of X-59 sonic booms. To evaluate the eight correction grades, mock X-59 acoustic recordings were generated using predicted ground-level X-59 sonic booms. These ground-level waveforms were created by Doebler [2] by propagating nearfield CFD solutions of the X-59 C612A configuration to the ground using PCBoom [3] (please see Acknowledgements and Refs. [4, 5, 2, 6]). To generate the mock acoustic recordings from those ground-level waveforms, they were further modified using turbulence filters developed during the NASA SonicBAT effort [7], post boom noise audio clips from the NASA SonicBAT tests [7], and ambient noise from the NASA QSF18 test [8, 9]. These mock acoustic recordings enabled evaluation of the ambient noise mitigation methods since the proper loudness levels of the X-59 waveforms in absence of ambient noise are known. Specifically, these known levels provide a benchmark against which the corrected loudness levels are compared, where the corrected loudness levels are computed when ambient noise is present within the waveforms. Importantly, similar analyses using in-field recordings are not possible since the proper loudness levels of the sonic boom waveforms in absence of ambient noise are unknowable when analyzing in-field recordings. Consequently, if additional analyses of ambient noise mitigation methods are needed, then use of mock recordings like those used here is recommended.

Sonic boom↗
NASA NTRSDate not supplied

Split-Step Simulations of Sonic Boom Propagation Beyond the Lateral Cutoff in a Turbulent Atmosphere

Recent flight tests during the Quiet Supersonic Flights 2018 (QSF18) study reported sonic booms heard outside of the primary carpet region. In the absence of turbulence, the lateral cutoff region separates the primary sonic boom carpet from the shadow zone, where the sonic boom signal experiences significant attenuation. However, when turbulence is present in the atmospheric boundary layer (ABL), additional scattering of the sonic boom to the shadow zone region occurs. A method is presented for simulating sonic boom propagation in a turbulent atmospheric boundary layer beyond the lateral cutoff region into the shadow zone. A split-step method is used to integrate a partially one-way equation for the acoustic pressure. Inhomogeneous turbulence, representative of the ABL, is generated in the computational domain with a Fourier synthesis approach. Distributions of several loudness metrics in the shadow zone region for a sonic boom N-wave and a shaped boom are examined. Increasing both turbulence root-mean-square velocity and integral length scale are found to increase the average loudness of booms in the shadow zone. (This research is supported by the Commercial Supersonic Technology Project of the National Aeronautics and Space Administration under Grant No. 80NSSC19K1685.)

sonic boom↗
NASA NTRS2022

Simulation and Application of Bayesian Dose Uncertainty Modeling for Low-Boom Community Noise Surveys

In dose-response modeling, failing to account for dose uncertainty can cause artificial flattening of the estimated slope of the dose-response curve. Previous analyses of NASA sonic boom community noise survey data utilized a Bayesian multilevel logistic regression model, which did not account for dose uncertainty. The current work extends the model to account for either classical or Berkson dose uncertainty. The extended model is applied to two simulated dose-response datasets to illustrate conditions under which the dose uncertainty term does and does not correct for the artificial flattening introduced by dose uncertainty. Finally, the extended model is applied to two previous NASA sonic boom community noise surveys. The resulting dose-response curve slope for the average participant is 5 to 10% steeper, but the difference in the noise dose that elicits a 5% highly annoyed response is small (less than 1 dB). The difference remains insignificant when producing population summary dose-response curves. Commentary is included on applicability to future X-59 low-boom community noise survey data modeling and analysis.

X-59↗
NASA NTRSDate not supplied

Effects of Dose Error and Sample Size on Sonic Boom Dose-response Curves

NASA will soon be collecting noise-annoyance community survey data as the X-59 aircraft flies supersonically over several communities in the USA. Sparse measurements of the X-59 sonic thumps will be used together with physics-based simulations to estimate noise doses at survey participant locations. These dose estimates have associated error that affects the accuracy of modeled dose-response curves, which can result in misestimation of annoyance. The precision in dose-response curves is also a consideration in selecting the number of survey participants. To enable pretest studies of dose error and precision, simulated dose-response data were generated based on NASA’s Quiet Supersonic Flights 2018 test. The data included various degrees of dose error and sample size. Frequentist multilevel logistic regression models were fit to the true and perturbed dose-response data. Simple proportional relationships were identified between the model parameters and the perturbation standard deviation. The summary dose-response curves illustrate the impact on accuracy if dose error is not accounted for in the model. The precision in the dose-response curves is also shown as the number of participants and degree of participation is varied. Finally, sampling variability is illustrated by showing the dose-response curves for several replicates with random draws of participants and errors.

X-59↗