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A new data processing technique for Rayleigh-Taylor instability growth experiments
Author(s) -
Yongteng Yuan,
Shaoyong Tu,
Wenyong Miao,
J. F. Wu,
Lifeng Wang,
Chuansheng Yin,
Yidan Hao,
Wenhua Ye,
Yongkun Ding,
Shaoen Jiang
Publication year - 2016
Publication title -
aip advances
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.421
H-Index - 58
ISSN - 2158-3226
DOI - 10.1063/1.4953846
Subject(s) - optical transfer function , computer science , image processing , rayleigh–taylor instability , optics , instability , data processing , convolution (computer science) , transfer function , spatial filter , data transmission , artificial intelligence , computer vision , physics , image (mathematics) , artificial neural network , computer network , electrical engineering , engineering , mechanics , operating system
Typical face-on experiments for Rayleigh-Taylor instability study involve the time-resolved radiography of an accelerated foil with line-of-sight of the radiography along the direction of motion. The usual method which derives perturbation amplitudes from the face-on images reverses the actual image transmission procedure, so the obtained results will have a large error in the case of large optical depth. In order to improve the accuracy of data processing, a new data processing technique has been developed to process the face-on images. This technique based on convolution theorem, refined solutions of optical depth can be achieved by solving equations. Furthermore, we discuss both techniques for image processing, including the influence of modulation transfer function of imaging system and the backlighter spatial profile. Besides, we use the two methods to the process the experimental results in Shenguang-II laser facility and the comparison shows that the new method effectively improve the accuracy of data processing

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