completed four projects, each with the objective to research sonic-boom signatures from a ground-and building-level perspective. The relatively compressed timeline of these projects resulted in many lessons learned. With each successive project, these lessons have been more relied upon and referenced. This paper provides a high-level overview of the relevant lessons learned and the importance of these lessons to future projects.
In support of the ongoing effort by the National Aeronautics and Space Administration (NASA) to bring supersonic commercial travel to the public, the NASA Armstrong Flight Research Center and the NASA Langley Research Center, in cooperation with other industry organizations, conducted a flight research experiment to identify the methods, tools, and best practices for a large-scale quiet (or "low") sonic boom community human response test. The name of the effort was Waveforms and Sonic boom Perception and Response (WSPR). Such tests will be applied to building a dataset that governing agencies such as the Federal Aviation Administration and the International Civil Aviation Organization will use to establish regulations for acceptable sound levels of overland sonic booms. The WSPR test was the first such effort that studied responses to non-traditional low sonic booms while the subject persons were in their own homes and performing daily activities.The WSPR test was a NASA collaborative effort with several industry partners, in response to a NASA Aeronautics Research Mission Directorate Research Opportunities in Aeronautics. The primary contractor was Wyle (El Segundo, California). Other partners included Gulfstream Aerospace Corporation
The problem of parameter estimation on hybrid-wing-body aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aerodynamic control eectors that act in coplanar motion. This adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of ight and simulation data must be performed in order to ascertain individual surface derivatives with any sort of mathematical condence. Non-standard control surface congurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, time-decorrelation techniques are applied to a model structure selected through stepwise regression for simulated and ight-generated lateral-directional parameter estimation data. A virtual eector model that uses mathematical abstractions to describe the multi-axis eects of clamshell surfaces is developed and applied. Comparisons are made between time history reconstructions and observed data in order to assess the accuracy of the regression model. The Cramér-Rao lower bounds of the estimated parameters are used to assess the uncertainty of the regression model relative to alternative models. Stepwise regression was found to be a useful technique for lateraldirectional model design for hybrid-wing-body aircraft, as suggested by available ight data. Based on the results of this study, linear regression parameter estimation methods using abstracted eectors are expected to perform well for hybrid-wing-body aircraft properly equipped for the task.
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