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Convolutional-SMART: a fast reconstruction technique for tomographic PIV

文献类型：期刊论文

作者Yang YF(杨云帆)1,2; He XY(何心怡)1,2; Wang HP(王洪平)2
刊名EXPERIMENTS IN FLUIDS
出版日期2025-09-06
卷号66期号:9页码:17
ISSN号0723-4864
DOI10.1007/s00348-025-04106-w
通讯作者Wang, Hongping(hpwang@imech.ac.cn)
英文摘要Tomographic reconstruction, a critical process for tomographic particle image velocimetry (Tomo-PIV), remains inefficient due to the required massive memories and high computational cost. In this work, a fast tomographic reconstruction technique is proposed to improve the efficiency significantly. The weighting coefficient, which represents the contribution of the voxel to the corresponding pixel intensity, is remodeled to be independent of the voxel's positions by artificially improving the particle image resolution. Consequently, the simultaneous multiplicative algebraic reconstruction technique (SMART) is re-implemented with convolution operations. The proposed method is named Convolutional-SMART (Conv-SMART). Moreover, the numerous convolution operations are accelerated using a graphics processing unit (GPU) to further reduce the reconstruction time. A synthetic three-dimensional 3D experiment with a vortex ring is carried out to numerically evaluate the precision and efficiency of the proposed method. The results show that the speed-up ratio of Conv-SMART to the original SMART reaches about five times faster in the central processing unit (CPU) environment and 15 times faster in the GPU environment without losing accuracy when the particle density is 0.05 particles per pixel (ppp) and the resolution is 20 voxels/mm. The speed-up ratio as a function of the particle density and resolution is also provided. Conv-SMART is also applied to the left ventricular Tomo-PIV experiment. The velocity field derived from Conv-SMART is consistent with that from SMART, whereas Conv-SMART achieves 50 times faster within the GPU.
分类号二类
WOS关键词VOLUME ; CYLINDER
资助项目National Natural Science Foundation of China[12588201] ; National Natural Science Foundation of China (NSFC) Excellence Research Group Program for 'Multiscale Problems in Nonlinear Mechanics'[12072348] ; NSFC[XDB0620102] ; Strategic Priority Research Program of Chinese Academy of Sciences
WOS研究方向Engineering ; Mechanics
语种英语
WOS记录号WOS:001564873600001
资助机构National Natural Science Foundation of China ; National Natural Science Foundation of China (NSFC) Excellence Research Group Program for 'Multiscale Problems in Nonlinear Mechanics' ; NSFC ; Strategic Priority Research Program of Chinese Academy of Sciences
其他责任者王洪平
源URL[http://dspace.imech.ac.cn/handle/311007/103686]  
专题力学研究所_非线性力学国家重点实验室
作者单位1.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech, Beijing 100190, Peoples R China;
推荐引用方式
GB/T 7714		 Yang YF,He XY,Wang HP. Convolutional-SMART: a fast reconstruction technique for tomographic PIV[J]. EXPERIMENTS IN FLUIDS,2025,66(9):17.
APA 杨云帆,何心怡,&王洪平.(2025).Convolutional-SMART: a fast reconstruction technique for tomographic PIV.EXPERIMENTS IN FLUIDS,66(9),17.
MLA 杨云帆,et al."Convolutional-SMART: a fast reconstruction technique for tomographic PIV".EXPERIMENTS IN FLUIDS 66.9(2025):17.

入库方式： OAI收割

来源：力学研究所

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