Wavelet spectrum analysis on energy transfer of multi-scale structures in wall turbulence

2009 ◽  
Vol 30 (4) ◽  
pp. 435-443 ◽  
Author(s):  
Zhen-yan Xia ◽  
Yan Tian ◽  
Nan Jiang
2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jay T. Lennon ◽  
Frank den Hollander ◽  
Maite Wilke-Berenguer ◽  
Jochen Blath

AbstractAcross the tree of life, populations have evolved the capacity to contend with suboptimal conditions by engaging in dormancy, whereby individuals enter a reversible state of reduced metabolic activity. The resulting seed banks are complex, storing information and imparting memory that gives rise to multi-scale structures and networks spanning collections of cells to entire ecosystems. We outline the fundamental attributes and emergent phenomena associated with dormancy and seed banks, with the vision for a unifying and mathematically based framework that can address problems in the life sciences, ranging from global change to cancer biology.


2021 ◽  
Vol 913 ◽  
Author(s):  
Patrick Doohan ◽  
Ashley P. Willis ◽  
Yongyun Hwang

Abstract


2016 ◽  
Vol 18 (5) ◽  
pp. 4134-4143 ◽  
Author(s):  
Linyin Yan ◽  
Yan Wan ◽  
Andong Xia ◽  
Sheng Hien Lin ◽  
Ran Huang

Multi-scale theoretical model and spectra simulation for dendrimers combining TD-DFT/DFT and semi-empirical methods.


2013 ◽  
Vol 715 ◽  
pp. 32-59 ◽  
Author(s):  
Lihao Zhao ◽  
Helge I. Andersson ◽  
Jurriaan J. J. Gillissen

AbstractTransfer of mechanical energy between solid spherical particles and a Newtonian carrier fluid has been explored in two-way coupled direct numerical simulations of turbulent channel flow. The inertial particles have been treated as individual point particles in a Lagrangian framework and their feedback on the fluid phase has been incorporated in the Navier–Stokes equations. At sufficiently large particle response times the Reynolds shear stress and the turbulence intensities in the spanwise and wall-normal directions were attenuated whereas the velocity fluctuations were augmented in the streamwise direction. The physical mechanisms involved in the particle–fluid interactions were analysed in detail, and it was observed that the fluid transferred energy to the particles in the core region of the channel whereas the fluid received kinetic energy from the particles in the wall region. A local imbalance in the work performed by the particles on the fluid and the work exerted by the fluid on the particles was observed. This imbalance gave rise to a particle-induced energy dissipation which represents a loss of mechanical energy from the fluid–particle suspension. An independent examination of the work associated with the different directional components of the Stokes force revealed that the dominating energy transfer was associated with the streamwise component. Both the mean and fluctuating parts of the Stokes force promoted streamwise fluctuations in the near-wall region. The kinetic energy associated with the cross-sectional velocity components was damped due to work done by the particles, and the energy was dissipated rather than recovered as particle kinetic energy. Componentwise scatter plots of the instantaneous velocity versus the instantaneous slip-velocity provided further insight into the energy transfer mechanisms, and the observed modulations of the flow field could thereby be explained.


2021 ◽  
Vol 58 (7) ◽  
pp. 446-459
Author(s):  
T. Fox ◽  
S. M. Lößlein ◽  
D. W. Müller ◽  
F. Mücklich

Abstract Fingerprints, a butterfly’s wings, or a lotus leaf: when it comes to surfaces, there is no such thing as coincidence in animated nature. Based on their surfaces, animals and plants control their wettability, their swimming resistance, their appearance, and much more. Evolution has optimized these surfaces and developed a microstructure that fits every need. It is all the more astonishing that, with regard to technical surfaces, man confines himself to random roughnesses or “smooth” surfaces. It is surely not a problem of a lack of incentives: structured surfaces have already provided evidence of optimizing friction and wear [1, 2, 3, 4], improving electrical contacts [5, 6], making implants biocompatible [7, 8], keeping away harmful bacteria [9], and much more. How come we continue counting on grinding, polishing, sandblasting, or etching? As so often, the problem can be found in economic cost effectiveness. It is possible to produce interesting structures such as those of the feather in Fig. 1. However, generating fine structures in the micro and nanometer range usually requires precise processing techniques. This is complex, time-consuming, and cannot readily be integrated into a manufacturing process. Things are different with Direct Laser Interference Patterning, DLIP) [10, 11]. This method makes use of the strong interference pattern of overlapped laser beams as a “stamp” to provide an entire surface area with dots, lines, or other patterns – in one shot. It thus saves time, allows for patterning speeds of up to 1 m2/min and does it without an elaborate pre- or post-treatment [10, 12]. The following article intends to outline how the method works, which structures can be generated, and how the complex multi-scale structures that nature developed over millions of years can be replicated in only one step.


2021 ◽  
Author(s):  
Harald Yndestad

<p><strong>Abstract</strong></p><p>A possible relation between plants period oscillations and the Earth´s temperature variability reveals deterministic variations in the Earth´s temperature variability. This study is based on a deterministic solar-lunar model, a wavelet spectrum analysis of global temperature data series from 1850 and a wavelet spectrum analysis of Greenland temperature (GISP-2) from 2000BC.</p><p> </p><p>The results reveal a period- and phase-relation between the Jovian planets, Total Solar Irradiation variability from 1700, global sea temperature variability from 1850 and Greenland temperature variability from 2000B.C. in a multidecadal spectrum of 4480 years. The results are explained by interference between accumulated solar-forced and lunar-forced periods in oceans. The climate response from solar-lunar forced periods explain Grand Solar minimum periods from 1000A.D. the Little Ice Age from 1640 to 1850, the Deep Freeze minimum at 1710 A.D. and the global temperature growth from 1850 to 2000. The solar-lunar model computes a modern global maximum temperature at 2030A.D. and an upcoming Grand Solar minimum at 2062A.D. and an upcoming deep temperature minimum at 2070A.D.</p><p> </p><p><strong>Keywords</strong>: Solar-lunar interference; Deep solar minima; Earth’s temperature variability; Global temperature minima.</p><p><strong> </strong></p>


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