Modeling and dynamic analysis of spiral bevel gear coupled system of intermediate and tail gearboxes in a helicopter.

The coupled dynamic model of the intermediate and tail gearboxes’ spiral bevel gear-oblique tail shaft-laminated membrane coupling was established by employing the hybrid modeling method of finite element and lumped mass. Among them, the dynamic equation of the shaft was constructed by Timoshenko beam; spiral bevel gears were derived theoretically by the lumped-mass method, where the effects of time-varying meshing stiffness, transmission error, external imbalance excitation and the like were considered simultaneously; laminated membrane coupling was simplified to a lumped parameter model, in which the stiffness was obtained by the finite element simulation and experiment. On this basis, the laminated membrane coupling and effects of several important parameters, including the unbalance value, tail rotor excitation, oblique tail shaft’s length and transmission error amplitude, on the system’s dynamic characteristics were discussed. The results showed that the influences of laminated membrane coupling and transmission error amplitude on the coupled system’s vibration response were prominent, which should be taken into consideration in the dynamic model. Due to the bending-torsional coupled effect, the lateral vibration caused by gear eccentricity would enlarge the oblique tail shaft’s torsional vibration; similarly, the tail rotor’s torsional excitation also varies the lateral vibration of the oblique tail shaft. The coupled effect between the eccentricity of gear pairs mainly hit the torsional vibration. Also, as the oblique tail shaft’s length increased, the torsional vibration of the oblique tail shaft tended to diminish while the axis orbit became larger. The research provides theoretical support for the design of the helicopter tail transmission system

3D Structure of Microwave Sources from Solar Rotation Stereoscopy vs Magnetic Extrapolations

We use rotation stereoscopy to estimate the height of a steady-state solar feature relative to the photosphere, based on its apparent motion in the image plane recorded over several days of observation. The stereoscopy algorithm is adapted to work with either one- or two-dimensional data (i.e. from images or from observations that record the projected position of the source along an arbitrary axis). The accuracy of the algorithm is tested on simulated data, and then the algorithm is used to estimate the coronal radio source heights associated with the active region NOAA 10956, based on multifrequency imaging data over 7 days from the Siberian Solar Radio Telescope near 5.7 GHz, the Nobeyama Radio Heliograph at 17 GHz, as well as one-dimensional scans at multiple frequencies spanning the 5.98--15.95 GHz frequency range from the RATAN-600 instrument. The gyroresonance emission mechanism, which is sensitive to the coronal magnetic field strength, is applied to convert the estimated radio source heights at various frequencies, h(f), to information about magnetic field vs. height B(h), and the results are compared to a magnetic field extrapolation derived from photospheric magnetic field observations obtained by Hinode and MDI. We found that the gyroresonant emission comes from the heights exceeding location of the third gyrolayer irrespectively on the magnetic extrapolation method; implications of this finding for the coronal magnetography and coronal plasma physics are discussed.Comment: 26 pages, 13 figures, ApJ accepte

A Solar Eruption Driven by Rapid Sunspot Rotation

We present the observation of a major solar eruption that is associated with fast sunspot rotation. The event includes a sigmoidal filament eruption, a coronal mass ejection, and a GOES X2.1 flare from NOAA active region 11283. The filament and some overlying arcades were partially rooted in a sunspot. The sunspot rotated at $\sim$10$^\circ$ per hour rate during a period of 6 hours prior to the eruption. In this period, the filament was found to rise gradually along with the sunspot rotation. Based on the HMI observation, for an area along the polarity inversion line underneath the filament, we found gradual pre-eruption decreases of both the mean strength of the photospheric horizontal field ($B_h$) and the mean inclination angle between the vector magnetic field and the local radial (or vertical) direction. These observations are consistent with the pre-eruption gradual rising of the filament-associated magnetic structure. In addition, according to the Non-Linear Force-Free-Field reconstruction of the coronal magnetic field, a pre-eruption magnetic flux rope structure is found to be in alignment with the filament, and a considerable amount of magnetic energy was transported to the corona during the period of sunspot rotation. Our study provides evidences that in this event sunspot rotation plays an important role in twisting, energizing, and destabilizing the coronal filament-flux rope system, and led to the eruption. We also propose that the pre-event evolution of $B_h$ may be used to discern the driving mechanism of eruptions

Inferring Line-of-Sight Velocities and Doppler Widths from Stokes Profiles of GST/NIRIS Using Stacked Deep Neural Networks

Obtaining high-quality magnetic and velocity fields through Stokes inversion is crucial in solar physics. In this paper, we present a new deep learning method, named Stacked Deep Neural Networks (SDNN), for inferring line-of-sight (LOS) velocities and Doppler widths from Stokes profiles collected by the Near InfraRed Imaging Spectropolarimeter (NIRIS) on the 1.6 m Goode Solar Telescope (GST) at the Big Bear Solar Observatory (BBSO). The training data of SDNN is prepared by a Milne-Eddington (ME) inversion code used by BBSO. We quantitatively assess SDNN, comparing its inversion results with those obtained by the ME inversion code and related machine learning (ML) algorithms such as multiple support vector regression, multilayer perceptrons and a pixel-level convolutional neural network. Major findings from our experimental study are summarized as follows. First, the SDNN-inferred LOS velocities are highly correlated to the ME-calculated ones with the Pearson product-moment correlation coefficient being close to 0.9 on average. Second, SDNN is faster, while producing smoother and cleaner LOS velocity and Doppler width maps, than the ME inversion code. Third, the maps produced by SDNN are closer to ME's maps than those from the related ML algorithms, demonstrating the better learning capability of SDNN than the ML algorithms. Finally, comparison between the inversion results of ME and SDNN based on GST/NIRIS and those from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory in flare-prolific active region NOAA 12673 is presented. We also discuss extensions of SDNN for inferring vector magnetic fields with empirical evaluation.Comment: 16 pages, 8 figure

Rapid Transition of Uncombed Penumbrae to Faculae during Large Flares

In the past two decades, the complex nature of sunspots has been disclosed with high-resolution observations. One of the most important findings is the "uncombed" penumbral structure, where a more horizontal magnetic component carrying most of Evershed Flows is embedded in a more vertical magnetic background (Solanki & Montavon 1993). The penumbral bright grains are locations of hot upflows and dark fibrils are locations of horizontal flows that are guided by nearly horizontal magnetic field. On the other hand, it was found that flares may change the topology of sunspots in $\delta$ configuration: the structure at the flaring polarity inversion line becomes darkened while sections of peripheral penumbrae may disappear quickly and permanently associated with flares (Liu et al. 2005). The high spatial and temporal resolution observations obtained with Hinode/ SOT provide an excellent opportunity to study the evolution of penumbral fine structure associated with major flares. Taking advantage of two near-limb events, we found that in sections of peripheral penumbrae swept by flare ribbons, the dark fibrils completely disappear, while the bright grains evolve into faculae that are signatures of vertical magnetic flux tubes. The corresponding magnetic fluxes measured in the decaying penumbrae show stepwise changes temporally correlated with the flares. These observations suggest that the horizontal magnetic field component of the penumbra could be straightened upward (i.e., turning from horizontal to vertical) due to magnetic field restructuring associated with flares, which results in the transition of penumbrae to faculae.Comment: 9 pages, 8 figures. Published in Ap

11β-Hydroxysteroid Dehydrogenase Type 1(11β-HSD1) mediates insulin resistance through JNK activation in adipocytes

Glucocorticoids are used to treat a number of human diseases but often lead to insulin resistance and metabolic syndrome. 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) is a key enzyme that catalyzes the intracellular conversion of cortisone to physiologically active cortisol. Despite the known role of 11β-HSD1 and active glucocorticoid in causing insulin resistance, the molecular mechanisms by which insulin resistance is induced remain elusive. The aim of this study is to identify these mechanisms in high fat diet (HFD) experimental models. Mice on a HFD were treated with 11β-HSD1 inhibitor as well as a JNK inhibitor. We then treated 3T3-L1-derived adipocytes with prednisone, a synthetic glucocorticoid, and cells with 11β-HSD1 overexpression to study insulin resistance. Our results show that 11β-HSD1 and JNK inhibition mitigated insulin resistance in HFD mice. Prednisone stimulation or overexpression of 11β-HSD1 also caused JNK activation in cultured adipocytes. Inhibition of 11β-HSD1 blocked the activation of JNK in adipose tissue of HFD mice as well as in cultured adipocytes. Furthermore, prednisone significantly impaired the insulin signaling pathway, and these effects were reversed by 11β-HSD1 and JNK inhibition. Our study demonstrates that glucocorticoid-induced insulin resistance was dependent on 11β-HSD1, resulting in the critical activation of JNK signaling in adipocytes