Seals with beaded whiskers-the majority of true seals (Phocids)-are able to trace even minute disturbance caused by prey fish in the ambient flow using only sensory input from their whiskers. The unique three-dimensional undulating morphology of seal whiskers has been associated with their capability of suppressing vortex-induced vibration and reducing drag. The exceptional hydrodynamic traits of seal whiskers are of great interest in renovating the design of aero-propulsion flow components and high-sensitivity flow sensors. It is essential to have well-documented data of seal whisker morphology with statistically meaningful generalization, as the solid foundation for whisker-inspired flow control applications. However, the available whisker morphology data is either incomplete, with measurements of only a few key parameters, or based on a very limited sample size in case studies. This work characterizes the morphology of 27 beaded seal whiskers (harbor seal and elephant seal), using high-resolution computer-tomography scanning at NASA's Glenn Research Center in Cleveland, OH. Over two thousand cross-sectional slices for every individual whisker sample are reconstructed, to generate three-dimensional morphology. This is followed by detailed statistical analysis of a set of key parameters, under an established framework (Hanke et al 2010 J. Exp. Biol. 213 2665-72). While the length parameters are generally consistent with previous studies, we note that the angle of incidence of elliptical cross-sections varies in a wide range, with a majority falling between [Formula: see text] and [Formula: see text]. Angles of incidence at both peaks and troughs appear to roughly follow a Gaussian distribution, but no clear preference of orientation is identified. We discuss the current knowledge of whisker-inspired flow studies, focusing on choices of morphology parameters. The new understanding of whisker morphology can better inform future design of high-sensitivity flow sensors and aero-propulsion flow structures.

This paper presents a model-based anomaly detection architecture designed for analyzing streaming transient aircraft engine measurement data. The technique calculates and monitors residuals between sensed engine outputs and model predicted outputs for anomaly detection purposes. Pivotal to the performance of this technique is the ability to construct a model that accurately reflects the nominal operating performance of the engine. The dynamic model applied in the architecture is a piecewise linear design comprising steady-state trim points and dynamic state space matrices. A simple curve-fitting technique for updating the model trim point information based on steady-state information extracted from available nominal engine measurement data is presented. Results from the application of the model-based approach for processing actual engine test data are shown. These include both nominal fault-free test case data and seeded fault test case data. The results indicate that the updates applied to improve the model trim point information also improve anomaly detection performance. Recommendations for follow-on enhancements to the technique are also presented and discussed.

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori (MAP) estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors (SSEE) in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate (CCR) for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Certain species of seals are able to faithfully detect minute disturbances in ambient water solely using their whiskers, which is attributed to the whiskers' undulating three-dimensional (3D) morphology. While previous studies have examined effects of key morphology parameters on the wake using scaled-up whisker models, it is unclear how the wake behaves when induced by a real undulating seal whisker. Real seal whiskers usually have a diameter of about one millimeter and present variation in size and bending curvature along the length, which are not being considered in designing scaled-up whisker-like models. In addition, how the whisker orientation affects the induced wake and vortex shedding needs to be clarified. This work examines the wake flow characteristics generated by a real elephant seal whisker (of undulating morphology) and a California sea lion whisker (of smooth morphology) in laboratory water channels at Reynolds numbers of 110 and 390, using snapshot particle image velocimetry (PIV) and time-resolved PIV methods. Results indicate that the reversed flow region is remarkably reduced and turbulence intensities are greatly suppressed behind the undulating whisker compared to that of the smooth whisker, when the major axis of the whisker cross-section is parallel with the incoming flow (i.e., the angle of attack or AOA is 0 ). While the vortex shedding frequency is reduced for both the undulating and smooth whiskers, the power spectral density is substantially increased at an AOA ¼ 90 in comparison to AOA ¼ 0 . Regardless of the AOA, the power spectral density is approximately 40% lower in the wake of the undulating whisker than that of the smooth whisker, indicating the favorable hydrodynamic feature of the undulating whisker. The extraordinary hydrodynamic traits of undulating seal whiskers is promising for renovating aero-propulsion flow components and designing high-sensitivity underwater flow sensors.

Lubrication forces depend to a high degree on elasticity, texture, charge, chemistry, and temperature of the interacting surfaces. Therefore, by appropriately designing surface properties, we may tailor lubrication forces to reduce friction, adhesion, and wear between sliding surfaces and control repulsion, assembly, and collision of interacting particles. Here, we show that variations of slippage on one of the contacting surfaces induce a lift force. We demonstrate the consequences of this force on the mobility of a cylinder traveling near a wall and show the emergence of particle oscillation and migration that would not otherwise occur in the Stokes flow regime. Our study has implications for understanding how inhomogeneous biological interfaces interact with their environment; we also propose a method of patterning surfaces for controlling the motion of nearby particles.