1,041 research outputs found

    Research on Low Frequency Noise Caused by Beat Vibration of Rotary Compressor

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    The discontinuity of low frequency noise caused by beat frequency vibration of rotary compressor is studied in this paper. Based on beat frequency theoretical analysis, a finite element model is established to simulate the electromagnetic harmonics. And the contributions of various compressor motor designs to beat frequency vibration are investigated, so the motor optimization design schemes are obtained. The tests show that the method proposed in the paper is effective to improve low frequency noise of the compressor

    Numerical and Experimental Research of Noise Reduction due to Low Frequency Pressure Fluctuation of Rotary Compressor

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    In order to reduce the noise level due to the low frequency pressure fluctuation associated with a rotary compressor, the noise mechanism and noise reduction solutions were conducted by using numerical and experimental methods. A 1D simulation model was established and a sensitivity analysis was conducted for the parameters associated with the low frequency pressure fluctuation of the rotary compressor. Then, a 3D CFD simulation model corresponding to the operation procedure of the rotary compressor was established and the working process of the rotary compressor was simulated. At the same time, the low frequency pressure fluctuation and the noise spectral characteristic were measured by using a refrigerant test fixture established in this work. Based on numerical and experimental research results, several noise reduction solutions and basic methods to restrain the low frequency pressure fluctuation were proposed and verified by using experimental method. A good improvement for the noise performance due to the low frequency pressure fluctuation was obtained. The work in this paper provides a reference and a foundation for the improvement of the noise due to the low frequency pressure fluctuation associated with rotary compressors

    ΛbΛc\Lambda_b \to \Lambda_c Form Factors from QCD Light-Cone Sum Rules

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    In this work, we calculate the transition form factors of Λb\Lambda_b decaying into Λc\Lambda_c within the framework of light-cone sum rules with the distribution amplitudes (DAs) of Λb\Lambda_b-baryon. In the hadronic representation of the correlation function, we have isolated both the Λc\Lambda_c and the Λc\Lambda_c^* states so that the ΛbΛc\Lambda_b \rightarrow \Lambda_c form factors can be obtained without ambiguity. We investigate the P-type and A-type current to interpolate the light baryons for a comparison since the interpolation current for the baryon state is not unique. We also employ three parametrization models for DAs of Λb\Lambda_b in the numerical calculation. We present the numerical predictions on the ΛbΛc\Lambda_b \rightarrow \Lambda_c form factors and the branching fractions, the averaged forward-backward asymmetry , the averaged final hadron polarization and the averaged lepton polarization of the ΛbΛcμ\Lambda_b \to \Lambda_c \ell\mu decays, as well as the ratio of branching ratios RΛcR_{\Lambda_c}, and the predicted RΛcR_{\Lambda_c} can be consistent with the LHCb data.Comment: 22 pages, 2figur

    Somatomotor-Visual Resting State Functional Connectivity Increases After Two Years in the UK Biobank Longitudinal Cohort

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    Functional magnetic resonance imaging (fMRI) and functional connectivity (FC) have been used to follow aging in both children and older adults. Robust changes have been observed in children, where high connectivity among all brain regions changes to a more modular structure with maturation. In older adults, prior work has identified changes in connectivity associated with the default mode network (DMN); other work has used brain age to predict pre-clinical Alzheimer's disease. In this work, we find an increasing connectivity between the Somatomotor (SMT) and Visual (VIS) Networks using the Power264 atlas in a longitudinal cohort of the UK Biobank (UKB). This cohort consists of 2,722 subjects, with scans being taken an average of two years apart. The average connectivity increase between SMT-VIS is 6.8% compared to the younger scan baseline (from ρ=0.39\rho=0.39 to ρ=0.42\rho=0.42), and occurs in male, female, older subject (>65>65 years old), and younger subject (<55<55 years old) groups. Among all inter-network connections, this average SMT-VIS connectivity is the best predictor of relative scan age, accurately predicting which scan is older 57% of the time. Using the full FC and a training set of 2,000 subjects, one is able to predict which scan is older 82.5% of the time when using the difference of FC between the two scans as input to a classifier. This previously under-reported relationship may shed light on normal changes in aging brain FC, identifies a potential confound for longitudinal studies, and proposes a new area for investigation, specifically the SMT-VIS connectivity.Comment: 12 pages, 10 figures, 3 table

    Effects of precipitation changes on aboveground net primary production and soil respiration in a switchgrass field

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    Switchgrass (Panicum virgatum L.) is widely selected as a model feedstock for sustainable replacement of fossil fuels and climate change mitigation. However, how climate changes, such as altered precipitation (PPT), will influence switchgrass growth and soil carbon storage potential have not been well investigated. We conducted a two-year PPT manipulation experiment with five treatments: −50%, −33%, +0%, +33%, and +50% of ambient PPT, in an “Alamo” switchgrass field in Nashville, TN. Switchgrass aboveground net primary production (ANPP), leaf gas exchange, and soil respiration (SR) were determined each growing season. Data collected from this study was then used to test whether switchgrass ANPP responds to PPT changes in a double asymmetry pattern as framed by Knapp et al. (2017), and whether it is held true for other ecosystem processes such as SR. Results showed that the wet (+33%, and +50%) treatments had little effects on ANPP and leaf gas exchange compared to the ambient precipitation treatment, regardless of fertilization or not. The −33% treatment did not change ANPP and leaf photosynthesis, but significantly decreased transpiration and enhanced water use efficiency (WUE). Only the −50% treatment significantly decreased ANPP and LAI, without changing leaf photosynthesis. SR generally decreased under the drought treatments and increased under the wet treatments, while there was no significant difference between the two drought treatments or between the two wet treatments. Our results demonstrate that switchgrass ANPP responded in a single negative asymmetry model to PPT changes probably due to relative high PPT in the region. However, even in such a mesic ecosystem, SR responded strongly to PPT changes in an “S” curve model, suggesting that future climate changes may have greater but more complex effects on switchgrass belowground than aboveground processes. The contrasting models for switchgrass ANPP and SR in response to PPT indicate that extreme wet or dry PPT conditions may shift ecosystem from carbon accumulation toward debt, and in turn provide government and policy makers with useful information for sustainable management of switchgrass
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