Engineering topics

Nathan B Cruze

Publications and source records attributed to Nathan B Cruze.

8 records

NASA NTRS2024

Summary and Annotated Bibliography of Measurement Error Corrections with Potential Application in Future Quesst Mission Community Noise Studies

This document is motivated by likely needs of the Quesst mission community response tests, which will culminate in data collection and estimation of dose-response regression relationships for consideration by domestic and international aviation regulators. Furthermore, basic research questions evaluating interactions between rates of community annoyance, dose levels, and indicators of the presence of rattle, vibration, and startle hinge on hypothesis testing in the context of regression models. For a variety of reasons, noise doses may be known only imprecisely and may not reflect the actual level experienced by responding subjects. These differences between true dose and estimated dose, be they systematic or random, constitute covariate measurement error. Available statistics literature speaks to the impacts of measurement error on regression models, both in terms of bias in estimated coefficients and predicted values, and in terms of the loss of statistical power for hypothesis testing. Given the particulars of a categorical annoyance response variable and a continuous noise dose predictor variable subject to measurement error during testing, the emphasis of this report is on findings and methods pertinent to generalized linear (and mixed) models likely to be employed during the Quesst mission community tests. We reach the following conclusions: 1. Of four reviewed methods, structural Bayesian measurement error models and simulation extrapolation (SIMEX) may be the most readily applicable to Quesst mission community noise study objectives. 2. If warranted, a linear measurement model can help model systematic sources of measurement error that the classical measurement error does not. 3. For its ready implementation and small additional input requirements, simulation extrapolation may be ideally suited for addressing secondary research questions involving interactions between annoyance, noise dose, and other factors through hypothesis testing. 4. For their flexibility and ability to propagate uncertainty, structural Bayesian hierarchical models have great appeal for mission purposes; some care may be needed in developing appropriate probability models describing actual noise exposure during testing. An annotated bibliography logs additional papers and resources that may be of value to analysts in other projects and disciplines.

Dose-Response Model↗

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 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 NTRSDate not supplied

Statistical Considerations for the Design and Execution of NASA's Community Noise Surveys

The World Health Organization defines community noise as noise emitted from all sources apart from noise at an industrial workplace. Example sources include neighborhood and construction noise, noise from road and rail, and air traffic noise. In particular, overland supersonic flights have been banned in the United States since the 1970s based on data accumulated during the 1960s; the degree of reported annoyance from the resulting sonic booms was a key factor leading to the prohibition. In subsequent years, scientific and engineering understanding has led to the potential to produce low amplitude sonic booms, or ‘sonic thumps’, during supersonic flight through aircraft design choices. Aircraft manufacturers have expressed renewed interest in producing supersonic commercial aircraft, but without appropriate changes to regulation, only overseas routes can be traveled supersonically. The National Aeronautics and Space Administration (NASA) will be flying the X-59 demonstrator aircraft in a series of community tests to begin in the 2024 fiscal year. In this presentation we provide some historical context for the current prohibitions on supersonic commercial flight. Using data collected during earlier NASA risk reduction tests, we demonstrate how generalized linear mixed models can be used to inform the functional dose-response response curve. Finally, we discuss some of the challenges in designing the future community studies and generalizing them to a nationally-representative dose-response curve. The study effort will be of national and international importance as the data and models prepared during the community tests will be provided to the International Civil Aviation Organization (ICAO) in order to help noise regulators determine if supersonic flight will be permitted over land once again and at what demonstrable noise levels.

Nathan B Cruze↗

NASA NTRSDate not supplied

Overview of Community Response Testing Campaign with NASA's X-59 Aircraft

Prohibition of civil supersonic flight over land became federal regulation in 1973, currently codified in 14 CFR Part 91.817. Of concern, the sonic booms that result when aircraft travel at supersonic speeds were deemed an untenable source of noise affecting populations directly under and near flight paths. Over the past fifty years, research in aircraft design and shaping has led to the prospect of low-noise supersonic flight. As part of its Quesst mission, NASA is building an experimental aircraft, the X-59, to demonstrate this capability. After completing flight test and design validation phases, NASA will field a national community testing campaign in order to collect data on how people perceive the sound from low-noise supersonic flight. The collected data will be provided to national and international regulators as they consider replacing the overland speed limit with a noise-based limit. This presentation provides an overview of the community test campaign, and identifies some of the key objectives, plans, and anticipated challenges.

X-59↗

NASA NTRSDate not supplied

Mitigating the Impacts of Measurement Error in the Quesst Mission Community Noise Study

Beginning in 2025, the NASA Quesst mission will conduct a series of community response tests involving flyovers of the X-59 aircraft at select localities across the United States. Several waves of a longitudinal survey will be administered over approximately one month of testing in order to capture perceptual responses to low-amplitude sonic booms, or “sonic thumps”. Simultaneously, noise exposure levels will be estimated by fusing model-based predictions with measurements taken from a sparse network of monitors in the region. As one of the aims of the study is to produce a dose-response curve, a regression model relating perceptual response to noise exposure levels, it is important to acknowledge the potential attenuation bias that results from measurement error in the estimated noise exposure levels. In this presentation we review and compare several methods for dealing with measurement error in generalized linear mixed models. The methods are demonstrated on simulated data and real data collected during past NASA risk reduction studies.

measurement error↗

NASA NTRSDate not supplied

Dose Error Correction Using Simulation Extrapolation for Community Noise Dose-Response Modeling

The objective of this work is to provide a framework to account and correct for dose error in dose-response modeling due to measurement uncertainty. Error in noise measurements, especially in the case of limited monitoring locations in a community, can lead to an attenuation or misestimation of parameters in dose-response models. This error can result in overpredicted annoyance at lower doses and underpredicted annoyance at higher doses. Simulated data in the present work are based on previous NASA community studies and incorporate a notional design for future studies with the X-59 aircraft. Several populations of different annoyance response sensitivities are included. Simulation extrapolation (SIMEX, Cook and Stefanski 1994) is used to correct for the dose error in a simple, fully pooled logistic regression. Results indicate the negative impact of attenuation is greatly diminished for all amounts of dose error considered, regardless of a population’s annoyance sensitivity. Therefore, SIMEX can help produce a more accurate dose-response relationship.

SIMEX↗

NASA NTRSDate not supplied

Modeling Measurement Error in Dose-Response Models of Community Annoyance to Low-Noise Supersonic Flight

The primary research goal of the forthcoming NASA Quesst mission community test campaign is to collect representative community response data in support of the development of supersonic overflight noise certification standards. Beginning in 2026, NASA will fly the novel X-59 demonstrator aircraft over select communities in United States in order to demonstrate the possibility of low-noise supersonic flight over land and to collect objective measurements and subjective data on the perceptual experience of this new noise source. It is believed that a regression of a binary perceptual response (‘highly annoyed’ or ‘not’) on estimated noise levels (doses, measured in decibels) will provide a useful dose-response relationship for regulators. However, as these estimated doses will be subject to measurement error, naïve estimators of regression coefficients are inconsistent and slopes may be subject to attenuation bias. In this presentation, I contrast functional modeling of measurement error via simulation extrapolation (SIMEX) with structural Bayesian measurement error models. These methods are applied to available data collected during two NASA risk reduction studies in California in 2011 and Texas in 2018. I’ll conclude noting that in the presence of nonnegligible measurement errors, probabilities of annoyance may be overpredicted for low noise levels and underpredicted for high noise levels, therefore, methods of correcting for measurement error will be necessary to improve the utility of the dose-response relationship for policy-making purposes.

simulation↗