This paper presents the development of an active on-blade vibration-reduction system using smart active blade tips (SABT), that are driven by a piezo-induced, bending-torsion coupled actuator. The actuator beam has a graphite substructure with surface bonded piezoceramic elements. A spanwise variation in both the bending-torsion coupling and the piezo element phasing is used to generate a pure tip twist. A small scale rotor, with 10% span active tips, was tested on the hover stand, at a reduced tip speed of Mach 0.25. At a mean thrust loading (CT/σ) of 0.07, and for an activation of 100 Vrms, SABT deflection amplitudes from 1.8 deg at 2/rev to 2.25 deg at 4/rev were achieved (half peak-to-peak). The rotor normal force measurements show a distinct coupling of the activation with the first and second flap frequencies of the rotor. The corresponding dynamic thrust, generated by a single active tip, relative to the steady thrust, ranges from 4.5% at 2/rev to 8.3% at 5/rev. For a 1/rev excitation, the single active tip generates a dynamic lift amplitude of 15% of the steady rotor thrust. The same actuator beam was used to test a rotor with controllable twist blades. The active twist blades used the same main blade section as the rotor blades with the active tips, and hence were not optimized for active twist configuration. Nonetheless, in hover, at a mean thrust loading (CT/σ) of 0.07, and with an activation of 100 Vrms, dynamic tip-twist amplitudes of 0.4 deg at 4/rev and 0.5 deg (at 5/rev) were achieved (half peak-to-peak).
Active rotorblade tips offer an alternative approach to the challenge of main rotor active vibration control. The tips are pitched with respect to the main blade via a piezo-driven bending-torsion coupled actuator beam that runs down the length of the blade. A Vlasov based, specialized one-dimensional finite beam element is developed to model the rotating actuator beam and is validated with the free-vibration and static forced response of 4:1 and 2:1 aspect ratio, bending-torsion coupled, active and passive plates. A one-eighth scale, reduced tip-speed rotor model (tip Mach 0.26), incorporating the bending-torsion actuator beam, has been previously hover tested (open loop). In these tests, blade tip deflections of the order of 2 • (half peak-to-peak) were achieved at 2, 3, 4, 5/rev with corresponding dynamic vertical blade root shear variations of the order of 10-20% of the nominal blade lift at 8 • collective (C T /σ = 0.07). The test results are used to validate a coupled actuator and elastic rotorblade model. The correlation of the predicted active blade-tip pitch deflections and the experimental data is within 20%. The predicted values for the active vertical root shears are within the same margin for 4 • and 6 • collective. Nomenclature A, B, D classical lamination stiffness matrices c chord c E ij elastic stiffness matrix, at constant electric field D i electric displacement, C m −2 d ij piezo constants, m V −1 = C N −1 e ij piezo constants, C m −2 , e ij = d ik c E kj
Compared to the huge microbial diversity in most mammals, human gut microbiomes have lost diversity while becoming specialized for animal-based diets – especially compared to chimps, their genetically closest ancestors. The lowered microbial diversity within the gut of westernized populations has also been associated with different kinds of chronic inflammatory diseases in humans. To further deepen our knowledge on phylogenetic and ecologic impacts on human health and fitness, we established the herein presented biobank as well as its comprehensive microbiota analysis. In total, 368 stool samples from 38 different animal species, including Homo sapiens, belonging to four diverse mammalian orders were collected at seven different locations and analyzed by 16S rRNA gene amplicon sequencing. Comprehensive data analysis was performed to (i) determine the overall impact of host phylogeny vs. diet, location, and ecology and to (ii) examine the general pattern of fecal bacterial diversity across captive mammals and humans.By using a controlled study design with captive mammals we could verify that host phylogeny is the most dominant driver of mammalian gut microbiota composition. However, the effect of ecology appears to be able to overcome host phylogeny and should therefore be studied in more detail in future studies. Most importantly, our study could observe a remarkable decrease of Spirochaetes and Prevotella in westernized humans and platyrrhines, which is probably not only due to diet, but also to the social behavior and structure in these communities.Our study highlights the importance of phylogenetic relationship and ecology within the evolution of mammalian fecal microbiota composition. Particularly, the observed decrease of Spirochaetes and Prevotella in westernized communities might be associated to lifestyle dependent rapid evolutionary changes, potentially involved in the establishment of dysbiotic microbiomes, which promote the etiology of chronic diseases.
Monitoring the health of a helicopter drive train enhances flight safety and reduces operating costs. Health and Usage Management Systems (HUMS) monitor the drive train by using accelerometers to measure component vibration. Algorithms process the time domain vibration data into various condition indicators (CI), which are used to determine component health via thresholding. 1 2For the rotating machinery, a standard set of CI are shaft order one, two and three (i.e. 1, 2 or 3 times the shaft RPM). Shaft order one (SO1) is indicative of an unbalance, where as higher shaft order can be used to detect a bent shaft or misalignment condition. In the case of bearings, CIs are envelope spectrum or cepstrum analysis of the ball, cage, inner race and outer race frequencies. There are a number of standard CI used for gear analysis, such as line elimination and resynthesis, side band modulation, gear misalignment, etc.In general, some method is used to set thresholds for these CIs: when the threshold is exceeded, maintenance is recommended. The HUMS system must balance the risk of setting the threshold too high such that a component may fail in flight versus the risk of setting the threshold too low, which results in additional maintenance cost. This paper covers a generalized process of optimally setting threshold for CI and fusing the information into an Health Indicator.It can be shown that the distributions of CI for shaft magnitude and bearing envelop energy are Rayleigh distribution. The normalized distance functions for these CIs are a Nakagami distribution with μ (shape parameter) of n (number of CI) and Ω (scale parameter) of 2 x 1/(2-π/2) x μ. For gear CIs, which are considered as Gaussian, the normalized distance function is again Nakagami, but with a μ of n/2 and Ω of n. Given the theoretical μ and Ω, a threshold for any set of CI can be generated resulting in system probability of false alarm (PFA). This is an optimal 1 1 1-4244-
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