a b s t r a c tWall pressure data acquired during flight tests at several flight conditions are analysed and the correlation and coherence lengths of the data reported. It is found that the correlation and coherence lengths are influenced by the origin of the structure producing the pressure and the frequency bandwidth over which the analyses are performed. It is shown how the frequency bandwidth biases the correlation length and how the convection of the pressure field might reduce the coherence measured between sensors. A convected form of the cross correlation and cross spectrum is introduced to compensate for the effects of convection. Coherence lengths measured in the streamwise direction appear much longer than expected. Coherent structures detected using the convected cross correlation do not exhibit an exponential coherent power decay.Published by Elsevier Ltd.

A psychoacoustic test was performed using simulated sounds from a distributed electric propulsion aircraft concept to help understand factors associated with human annoyance. A design space spanning the number of high-lift leading edge propellers and their relative operating speeds, inclusive of time varying effects associated with motor controller error and atmospheric turbulence, was considered. It was found that the mean annoyance response varies in a statistically significant manner with the number of propellers and with the inclusion of time varying effects, but does not differ significantly with the relative RPM between propellers. An annoyance model was developed, inclusive of confidence intervals, using the noise metrics of loudness, roughness, and tonality as predictors.

One of the key benefits of fu h.dwarey ,ple)ntations of certain ficai Neural Networks (ANNs) is their apparen 'built-in'fault'tolerance, which make thewpotentiO candidates for critical tasks with hi h reliability requirements. This pape inveitigates the fault-tolerance characteristics df time continuous, recurrent ANNs that c be used to solve optimization problems. The perform ce of these networks is first illus, ated by using ellknown model problems like the TraveIng Salesman Problem and theAssignment Prgblem. The ANNs are then subjected to up to 3 simultaneous "stuck-at-1 or "stuck-at-0" faults for network sizes of up to 900 "neurons." The effect of these faults on the performance is demonstrated and the cause for the observed fault-tolerance is discussed. An application is presented in which a network performs a critical task for a realftime distributed processing system by generating new task allocations during the reconfigpration of the system. The performance degradation of the ANN under the presence of fa4lts is investigated by largescale simulations and the potential benefits of delegating a critical task to a fault-tolerant network are discussed.

Researchers at NASA Langley Research Center have extensive experience using active structural acoustic control (ASAC) for aircraft interior noise reduction. One aspect of ASAC involves the selection of optimum locations for microphone sensors and force actuators. This paper explains the importance of sensor/actuator selection, reviews optimization techniques, and summarizes experimental and numerical results.Three combinatorial optimization problems are described. Two involve the determination of the number and position of piezoelectric actuators, and the other involves the determination of the number and location of the sensors. For each case, a solution method is suggested, and typical results are examined. The first case, a simplified problem with simulated data, is used to illustrate the method. The second and third cases are more representative of the potential of the method and use measured data. The three case studies and laboratory test results establish the usefulness of the numerical methods.

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