Tensor interpolation is a key step in the processing algorithms of diffusion tensor imaging (DTI), such as registration and tractography. The diffusion tensor (DT) in biological tissues is assumed to be positive defin...Tensor interpolation is a key step in the processing algorithms of diffusion tensor imaging (DTI), such as registration and tractography. The diffusion tensor (DT) in biological tissues is assumed to be positive definite. However, the tensor interpolations in most clinical applications have used a Euclidian scheme that does not take this assumption into account. Several Rie-mannian schemes were developed to overcome this limitation. Although each of the Riemannian schemes uses different metrics, they all result in a ‘fixed’ interpolation profile that cannot adapt to a variety of diffusion patterns in biological tissues. In this paper, we propose a DT interpolation scheme to control the interpolation profile, and explore its feasibility in clinical applications. The profile controllability comes from the non-uniform motion of interpolation on the Riemannian geodesic. The interpolation experiment with medical DTI data shows that the profile control improves the interpolation quality by assessing the reconstruction errors with the determinant error, Euclidean norm, and Riemannian norm.展开更多
The fluid resonance of a moonpool freely heaving in a beam sea is studied by an in-house constrained interpolation profile(CIP)code.Generally,the moonpool behaves as in the piston mode with a narrow opening.The numeri...The fluid resonance of a moonpool freely heaving in a beam sea is studied by an in-house constrained interpolation profile(CIP)code.Generally,the moonpool behaves as in the piston mode with a narrow opening.The numerical studies are carried out for a wide range of the incident waves,and a new secondary resonant region is identified in the low frequency region of the incident waves,besides the ordinary main resonant region.Numerical results demonstrate that the horizontal wave forces are significant in the secondary resonant region,although the resonant wave elevations are less remarkable than those of the main resonant region.It is concluded that the fluid resonance of the low frequency is excited mainly by the heave motion of the moonpool.Parameter studies of the moonpool draft and the gap width of the moonpool based on the fluid resonance are also performed.展开更多
In this study,a computational framework in the field of artificial intelligence was applied in computational fluid dynamics(CFD)field.This Framework,which was initially proposed by Google Al department,is called"...In this study,a computational framework in the field of artificial intelligence was applied in computational fluid dynamics(CFD)field.This Framework,which was initially proposed by Google Al department,is called"TensorFlow".An improved CFD model based on this framework was developed with a high-order difference method,which is a constrained interpolation profile(CIP)scheme for the base flow solver of the advection term in the Navier-Stokes equations,and preconditioned conjugate gradient(PCG)method was implemented in the model to solve the Poisson equation.Some new features including the convolution,vectorization,and graphics processing unit(GPU)acceleration were implemented to raise the computational efficiency.The model was tested with several benchmark cases and shows good performance.Compared with our former CIP-based model,the present Tensor Flow-based model also shows significantly higher computational efficiency in large-scale computation.The results indicate TensorFlow could be a promising framework for CFD models due to its ability in the computational acceleration and convenience for programming.展开更多
基金Project (No. 60772092) supported by the National Natural Science Foundation of China
文摘Tensor interpolation is a key step in the processing algorithms of diffusion tensor imaging (DTI), such as registration and tractography. The diffusion tensor (DT) in biological tissues is assumed to be positive definite. However, the tensor interpolations in most clinical applications have used a Euclidian scheme that does not take this assumption into account. Several Rie-mannian schemes were developed to overcome this limitation. Although each of the Riemannian schemes uses different metrics, they all result in a ‘fixed’ interpolation profile that cannot adapt to a variety of diffusion patterns in biological tissues. In this paper, we propose a DT interpolation scheme to control the interpolation profile, and explore its feasibility in clinical applications. The profile controllability comes from the non-uniform motion of interpolation on the Riemannian geodesic. The interpolation experiment with medical DTI data shows that the profile control improves the interpolation quality by assessing the reconstruction errors with the determinant error, Euclidean norm, and Riemannian norm.
基金the Fundamental Research Funds for the Central Universities(Grant No.HIT.OCEF.2021037)the Taishan Scholars Project of Shandong Province(Grant No.tsqn201909172)the University Young Innovational Team Program,Shandong Province(Grant No.2019KJN003).
文摘The fluid resonance of a moonpool freely heaving in a beam sea is studied by an in-house constrained interpolation profile(CIP)code.Generally,the moonpool behaves as in the piston mode with a narrow opening.The numerical studies are carried out for a wide range of the incident waves,and a new secondary resonant region is identified in the low frequency region of the incident waves,besides the ordinary main resonant region.Numerical results demonstrate that the horizontal wave forces are significant in the secondary resonant region,although the resonant wave elevations are less remarkable than those of the main resonant region.It is concluded that the fluid resonance of the low frequency is excited mainly by the heave motion of the moonpool.Parameter studies of the moonpool draft and the gap width of the moonpool based on the fluid resonance are also performed.
基金Supported by the National Natural Science Foundation of China(Grant No.51679212,51979245).
文摘In this study,a computational framework in the field of artificial intelligence was applied in computational fluid dynamics(CFD)field.This Framework,which was initially proposed by Google Al department,is called"TensorFlow".An improved CFD model based on this framework was developed with a high-order difference method,which is a constrained interpolation profile(CIP)scheme for the base flow solver of the advection term in the Navier-Stokes equations,and preconditioned conjugate gradient(PCG)method was implemented in the model to solve the Poisson equation.Some new features including the convolution,vectorization,and graphics processing unit(GPU)acceleration were implemented to raise the computational efficiency.The model was tested with several benchmark cases and shows good performance.Compared with our former CIP-based model,the present Tensor Flow-based model also shows significantly higher computational efficiency in large-scale computation.The results indicate TensorFlow could be a promising framework for CFD models due to its ability in the computational acceleration and convenience for programming.
