97,709 research outputs found

    Engineering the accurate distortion of an object's temperature-distribution signature

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    It is up to now a challenge to control the conduction of heat. Here we develop a method to distort the temperature distribution signature of an object at will. As a result, the object accurately exhibits the same temperature distribution signature as another object that is predetermined, but actually does not exist in the system. Our finite element simulations confirm the desired effect for different objects with various geometries and compositions. The underlying mechanism lies in the effects of thermal metamaterials designed by using this method. Our work is of value for applications in thermal engineering.Comment: 11 pages, 4 figure

    Time dependent intrinsic correlation analysis of temperature and dissolved oxygen time series using empirical mode decomposition

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    In the marine environment, many fields have fluctuations over a large range of different spatial and temporal scales. These quantities can be nonlinear \red{and} non-stationary, and often interact with each other. A good method to study the multiple scale dynamics of such time series, and their correlations, is needed. In this paper an application of an empirical mode decomposition based time dependent intrinsic correlation, \red{of} two coastal oceanic time series, temperature and dissolved oxygen (saturation percentage) is presented. The two time series are recorded every 20 minutes \red{for} 7 years, from 2004 to 2011. The application of the Empirical Mode Decomposition on such time series is illustrated, and the power spectra of the time series are estimated using the Hilbert transform (Hilbert spectral analysis). Power-law regimes are found with slopes of 1.33 for dissolved oxygen and 1.68 for temperature at high frequencies (between 1.2 and 12 hours) \red{with} both close to 1.9 for lower frequencies (time scales from 2 to 100 days). Moreover, the time evolution and scale dependence of cross correlations between both series are considered. The trends are perfectly anti-correlated. The modes of mean year 3 and 1 year have also negative correlation, whereas higher frequency modes have a much smaller correlation. The estimation of time-dependent intrinsic correlations helps to show patterns of correlations at different scales, for different modes.Comment: 35 pages with 22 figure

    Lagrangian Cascade in Three-Dimensional Homogeneous and Isotropic Turbulence

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    In this work, the scaling statistics of the dissipation along Lagrangian trajectories are investigated by using fluid tracer particles obtained from a high resolution direct numerical simulation with ReĪ»=400Re_{\lambda}=400. Both the energy dissipation rate Ļµ\epsilon and the local time averaged ĻµĻ„\epsilon_{\tau} agree rather well with the lognormal distribution hypothesis. Several statistics are then examined. It is found that the autocorrelation function Ļ(Ļ„)\rho(\tau) of lnā”(Ļµ(t))\ln(\epsilon(t)) and variance Ļƒ2(Ļ„)\sigma^2(\tau) of lnā”(ĻµĻ„(t))\ln(\epsilon_{\tau}(t)) obey a log-law with scaling exponent Ī²ā€²=Ī²=0.30\beta'=\beta=0.30 compatible with the intermittency parameter Ī¼=0.30\mu=0.30. The qqth-order moment of ĻµĻ„\epsilon_{\tau} has a clear power-law on the inertial range 10<Ļ„/Ļ„Ī·<10010<\tau/\tau_{\eta}<100. The measured scaling exponent KL(q)K_L(q) agrees remarkably with qāˆ’Ī¶L(2q)q-\zeta_L(2q) where Ī¶L(2q)\zeta_L(2q) is the scaling exponent estimated using the Hilbert methodology. All these results suggest that the dissipation along Lagrangian trajectories could be modelled by a multiplicative cascade.Comment: 10 pages with 7 figures accepted for Journal of Fluid Mechanics as Rapid
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