A least‐squares migration algorithm is presented that reduces the migration artifacts (i.e., recording footprint noise) arising from incomplete data. Instead of migrating data with the adjoint of the forward modeling operator, the normal equations are inverted by using a preconditioned linear conjugate gradient scheme that employs regularization. The modeling operator is constructed from an asymptotic acoustic integral equation, and its adjoint is the Kirchhoff migration operator. We tested the performance of the least‐squares migration on synthetic and field data in the cases of limited recording aperture, coarse sampling, and acquisition gaps in the data. Numerical results show that the least‐squares migrated sections are typically more focused than are the corresponding Kirchhoff migrated sections and their reflectivity frequency distributions are closer to those of the true model frequency distribution. Regularization helps attenuate migration artifacts and provides a sharper, better frequency distribution of estimated reflectivity. The least‐squares migrated sections can be used to predict the missing data traces and interpolate and extrapolate them according to the governing modeling equations. Several field data examples are presented. A ground‐penetrating radar data example demonstrates the suppression of the recording footprint noise due to a limited aperture, a large gap, and an undersampled receiver line. In addition, better fault resolution was achieved after applying least‐squares migration to a poststack marine data set. And a reverse vertical seismic profiling example shows that the recording footprint noise due to a coarse receiver interval can be suppressed by least‐squares migration.

A theoretical model based on multiphase flow theory of gas-particle is developed to evaluate the granular particle damping characteristics. Expressions for the drag forces of the equivalent viscous damping and the Coulomb friction damping are formulated respectively. The nonlinear free vibration of an exemplified cantilever particle-damping beam is analyzed by using the averaging method based on the first approximation. Numerical results are also presented to illustrate general characteristics of the particle-damping beam. An experimental verification is performed, and a good correlation between the theoretical results and the experimental data shows that the theoretical work in this paper is valid.

No abstract

No abstract

No abstract

No abstract

This paper presents a composite vibration control method that uses a double-decked floating raft isolation system and particle dampers to control the severe vibration of a heavy compressor set. In view of the structural characteristics of the compressor set, a mechanical impedance method is employed to investigate the acceleration transfer ratios of the double-decked floating raft isolation system, and to design three isolating schemes. Numerical results indicate that the particle damping technology does not disturb the isolating performance of the double-decked floating raft isolation system while reducing only its acceleration amplitude. To improve the damping performance of particle dampers, an anti-resonance method and a co-simulation technique are used to optimize the installation location of the particle dampers, as the damping effect is related to the vibrating velocity at the damper’s position. Furthermore, two types of particle damper—cylindrical and cuboid—are designed, based on conclusions drawn from experiments using the anti-resonance method. The damping effectiveness of the particle damper scheme is also examined using the co-simulation technique; results indicate that the proposed installation scheme can effectively suppress the vibration of the compressor rack. In addition, the presented schemes using the composite vibration control method are verified and compared in on-site experiments, and results demonstrate that the third isolating scheme presented, combined with particle damping technology, is best in controlling vibration of the compressor set.

No abstract