Time-space domain nearfield acoustical holography for visualizing normal velocity of sources

2020 ◽  
Vol 139 ◽  
pp. 106363
Author(s):  
Nicolas Aujogue ◽  
Annie Ross ◽  
Jean-Michel Attendu
2000 ◽  
Author(s):  
Earl G. Williams

Abstract Nearfield Acoustical Holography (NAH) is an inverse problem in wave propagation which has found applications to both interior and exterior noise control problems. We can view the fundamental equation of NAH in the spatial frequency domain as a linear equation, p=Gv, where p is the measured pressure, v is the unknown normal velocity (usually on the surface of a vibrator), and G is the known transfer function. NAH inverts this equation solving for the velocity. However, this equation is ill-posed since small changes in p usually lead to large changes in v. Thus the need for regularization of the inversion. We will discuss regularization techniques applied to NAH, and will compare the errors associated with several regularization schemes; Tikhonov, conjugate gradient, Landweber iteration and a simple exponential filter approach (which appears to provide the best results). Furthermore, in an effort to illuminate the physical propagation mechanisms of NAH, we will discuss these approaches in the light of k-space.


Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. T175-T193 ◽  
Author(s):  
Enjiang Wang ◽  
Jing Ba ◽  
Yang Liu

It has been proved that the implicit spatial finite-difference (FD) method can obtain higher accuracy than explicit FD by using an even smaller operator length. However, when only second-order FD in time is used, the combined FD scheme is prone to temporal dispersion and easily becomes unstable when a relatively large time step is used. The time-space domain FD can suppress the temporal dispersion. However, because the spatial derivatives are solved explicitly, the method suffers from spatial dispersion and a large spatial operator length has to be adopted. We have developed two effective time-space-domain implicit FD methods for modeling 2D and 3D acoustic wave equations. First, the high-order FD is incorporated into the discretization for the second-order temporal derivative, and it is combined with the implicit spatial FD. The plane-wave analysis method is used to derive the time-space-domain dispersion relations, and two novel methods are proposed to determine the spatial and temporal FD coefficients in the joint time-space domain. First, we fix the implicit spatial FD coefficients and derive the quadratic convex objective function with respect to temporal FD coefficients. The optimal temporal FD coefficients are obtained by using the linear least-squares method. After obtaining the temporal FD coefficients, the SolvOpt nonlinear algorithm is applied to solve the nonquadratic optimization problem and obtain the optimized temporal and spatial FD coefficients simultaneously. The dispersion analysis, stability analysis, and modeling examples validate that the proposed schemes effectively increase the modeling accuracy and improve the stability conditions of the traditional implicit schemes. The computational efficiency is increased because the schemes can adopt larger time steps with little loss of spatial accuracy. To reduce the memory requirement and computational time for storing and calculating the FD coefficients, we have developed the representative velocity strategy, which only computes and stores the FD coefficients at several selected velocities. The modeling result of the 2D complicated model proves that the representative velocity strategy effectively reduces the memory requirements and computational time without decreasing the accuracy significantly when a proper velocity interval is used.


Sign in / Sign up

Export Citation Format

Share Document