Research on the influence of ring rib arrangement on vibration and acoustic radiation of cylindrical shell

Based on the thin shell theory and the three-dimensional Sono-elasticity theory, the finite element method is used to study the transmission and variation characteristics of the cylindrical shell, in the case of non-ribs, single ring ribs and multi-ring ribs. The influence of different ribbed forms on the acoustic radiation is also analyzed. The result shows that the ring rib structure can suppress the transmission of medium and high frequency vibration, and the maximum attenuation frequency of the cylindrical shell is changed. The maximum attenuation frequency increases as the number of ring ribs increases. The vibration attenuation of the structure under multi-ribbed is higher than the single-ribbed at the middle frequency band, but lower than the single-ribbed at the high frequency band. The multi- ribbed structure can reduce the low-frequency radiated acoustic power of the structure, but it will affect the high-frequency acoustic radiation characteristics of the structure

Dynamic of Soil Mesofauna of Fixed Sand Dunes on the Songnen Grasslands, Northeastern China

Grasslands cover vast land areas in semi-arid and semi-humid regions. Sand dunes, most of which are fixed sand dunes, form a large portion of grasslands. Vegetation on fixed sand dunes is an important part of grassland ecosystem productivity, and topographic position is one of the important factors resulting in the differences among vegetation, soil, etc. (Sakai and Ohsawa, 1994; Nagamatsu and Miura, 1997). An important component of soil fauna ecology is to analyze the distribution of soil fauna and its influencing factors. On the small scale, the ozone factors become the dominant factor affecting the soil fauna (Frouz et al., 2011). Topographic position is an important factor affecting the distribution of soil fauna on fixed sand dunes (Xin et al., 2013). This paper takes fixed sand dunes on the Songnen Grasslands as the research objects, and aims to determine the structure and diversity of soil mesofauna on the different positions of the fixed sand dunes

Analysis of hydrodynamic noise characteristics of rudder-wing

The flow field and sound field of trapezoidal rudder-wing under different rudder angles are numerically predicted by CFD LES theory, Lighthill acoustic analogy theory and vibro-acoustic theory. And characteristics of hydrodynamic noise including flow noise and vibroacoustics under hydrodynamic excitations are analyzed. Results show that: at the same speed, the hydrodynamic noise raises with the increase of rudder angle; sound pressure level spectrum band of flow noise is wide and there is no obvious dominant frequency while there is a very obvious peak value of vibroacoustics under hydrodynamic excitations corresponding to the first order modal frequency in the band of 520-530 Hz; sound intensity at the front of leading edge and after trailing edge is higher than that at both sides of rudder-wing; the vibration of trailing edge is large, so it is the concentrated area of noise source

Study on dynamic characteristics of double cylinder double acting bilge pump transmission

In view of the complex structure of the ship bilge pump, the excitation source in the process of work is difficult to accurately determine the fault condition of the bilge pump through the vibration test data. Based on the theory of multi - body dynamics, rotor dynamics and electrical mechanics, the kinematics and kinetic equations of the bilge pump drive are established, and the dynamics, kinematics and vibration characteristics of bottom Pump drive analysis of the cabin is carried out. The frequency of the excitation force corresponding to the transmission mechanism is deduced, and the frequency of the excitation force of the main transmission is calculated

Phagraphene: A Low-energy Graphene Allotrope composed of 5-6-7 Carbon Rings with Distorted Dirac Cones

Using systematic evolutionary structure searching we propose a new carbon allotrope, phagraphene, standing for penta-hexa-hepta-graphene, because the structure is composed of 5-6-7 carbon rings. This two-dimensional (2D) carbon structure is lower in energy than most of the predicted 2D carbon allotropes due to its sp2-hybridization and density of atomic packing comparable to graphene. More interestingly, the electronic structure of phagraphene has distorted Dirac cones. The direction-dependent cones are further proved to be robust against external strain with tunable Fermi velocities.Comment: 5 pages, 3 figure

Numerical simulation of fluctuation pressure with liquid-filled pipes based on large eddy simulation method

Pipeline is an important part of mechanical system on ship. Fluctuation pressure produced on the pipe wall is a significant source of noise, and more and more scholars pay attention to it. In this paper, by using large eddy simulation and subgrid turbulence theory, pipeline fluctuation pressure simulation model is established, and influence of flow velocity, wall roughness and step offset of pipeline connection on pipe fluctuation pressure are studied. This provides theoretical guidance for low-noise installation and maintenance of ship piping system

Noise-Resistant Spectral Features for Retrieving Foliar Chemical Parameters

Foliar chemical constituents are important indicators for understanding vegetation growing status and ecosystem functionality. Provided the noncontact and nondestructive traits, the hyperspectral analysis is a superior and efficient method for deriving these parameters. In practice, thespectral noise issue significantly impacts the performance of the hyperspectral retrieving system. To systematically investigate this issue, by introducing varying levels of noise to spectral signals, an assessment on noiseresistant capability of spectral features and models for retrieving concentrations of chlorophyll, carotenoids, and leaf water content was conducted. Given the continuous waveletanalysis (CWA) showed superior performance in extracting critical information associating plants biophysical and biochemical status in recent years, both wavelet features (WFs) and some conventional features (CFs) were chosen for the test. Two datasets including a leaf optical properties experiment dataset (n = 330), and a corn leaf spectral experiment dataset (n = 213) were used for analysis and modeling. The results suggested that the WFs had stronger correlations with all leaf chemical parameters than the CFs. According to an evaluation by decay rate of retrieving error that indicates noise-resistant capability, both WFs and CFs exhibited strong resistance to spectral noise. Particularly for WFs, the noise-resistant capability is relevant to the scale of the features. Based on the identified spectral features, both univariate and multivariate retrieving models were established and achieved satisfactory accuracies. Synthesizing the retrieving accuracy, noise resistivity, and model’s complexity, the optimal univariate WF-models were recommended in practice for retrieving leaf chemical parameters

A method for incremental discovery of financial event types based on anomaly detection

Event datasets in the financial domain are often constructed based on actual application scenarios, and their event types are weakly reusable due to scenario constraints; at the same time, the massive and diverse new financial big data cannot be limited to the event types defined for specific scenarios. This limitation of a small number of event types does not meet our research needs for more complex tasks such as the prediction of major financial events and the analysis of the ripple effects of financial events. In this paper, a three-stage approach is proposed to accomplish incremental discovery of event types. For an existing annotated financial event dataset, the three-stage approach consists of: for a set of financial event data with a mixture of original and unknown event types, a semi-supervised deep clustering model with anomaly detection is first applied to classify the data into normal and abnormal events, where abnormal events are events that do not belong to known types; then normal events are tagged with appropriate event types and abnormal events are reasonably clustered. Finally, a cluster keyword extraction method is used to recommend the type names of events for the new event clusters, thus incrementally discovering new event types. The proposed method is effective in the incremental discovery of new event types on real data sets.Comment: 11 pages,4 figure