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Synthetic Turbulence Constructed by Self-Learning Fractal Interpolation

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摘要 A self-learning fractal interpolation algorithm to construct synthetic fields with statistical properties close to real turbulence is proposed.Different from our previous work[Phys.Rev.E 84(2011)026328,82(2010)036311],the position mapping and stretching factors between the adjacent large and small scales are learned from the initial information.Using this method,a turbulence-like field with K41 spectra and without dissipation is constructed well through a coarse grid velocity signal from one experiment's data.After filtering the interpolated signal appropriately,the probability distribution of velocity,velocity structure functions and the anomalous scaling law of the synthetic field are close to those of the original signal.
作者 WANG Yan-Zhi ZHANG Zhi-Xiong SHI Yi-Peng SHE Zhen-Su 王彦之;张志雄;史一蓬;佘振苏(State Key Laboratory of Turbulence and Complex Systems and College of Engineering,Peking University,Beijing 100871;Beijing Aeronautical Science and Technology Research Institute of COMAC Future Science&Technology Park,Changping District,Beijing 102211)
出处 《Chinese Physics Letters》 SCIE CAS CSCD 2012年第10期125-128,共4页 中国物理快报(英文版)
基金 Supported by the National Basic Research Program of China under Grant No 2009CB724100.
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