Rayleigh-Wave Dispersion Analysis and Inversion Based on the Rotation

Abstract

Rotational observation is essential for a comprehensive description of the ground motion, and can provide additional wave-field information. With respect to the three typical layered models in shallow engineering geology, under the assumption of linear small deformation, we simulate the 2-dimensional radial, vertical, and rotational components of the wave fields and analyze the different characteristics of Rayleigh wave dispersion recorded for the rotational and translational components. Then, we compare the results of single-component inversion with the results of multi-component joint inversion. It is found that the rotational component has wider spectral bands and more higher modes than the translational components, especially at high frequencies; the rotational component has better anti-interference performance in the noisy data test, and it can improve the inversion accuracy of the shallow shear-wave velocity. The field examples also show the significant advantages of the joint utility of the translational and rotational components, especially when a low-velocity layer exists. Rotational observation shall be beneficial for shallow surface-wave exploration.

Rayleigh wave through half space semiconductor solid with temperature dependent properties

“…Therefore, m is the penetration depth, c = w x is the dimensionless phase velocity, ξ is the wavenumber and ω is the angular frequency. Now by putting the solution of Rayleigh wave in equation (16)(17)(18)(19), we get,…”

“…By coupling a piezoelectric material to a semiconductor, it is possible to convert the mechanical energy of this wave into electrical energy, which can be used to power small electronic devices [16,17]. This has potential applications in fields such as wireless sensor networks and internet of things (IoT) devices, which require low-power, selfcontained energy sources described by Sun et al [18]. Rayleigh waves are a type of surface wave that propagates along the surface of solids.…”

Inversion of Rayleigh Wave Dispersion Curves Via BP Neural Network and PSO

“…Fourthly, controlling the inversion parameters can be considered. All-parameters Rayleigh wave inversion requires reconstructing the S-wave velocity, the P-wave velocity, the density and the thickness of each stratum simultaneously (Sun et al, 2022;Yang & Yuen, 2021). While its often difficult to obtain the exact solution of each parameter when the stratification of the strata is finer.…”

“…The second category is the completely nonlinear global optimization algorithm, including the global optimization algorithm based on random sampling in the solution space and the random search algorithm based on meta heuristic. The former is represented by Monte Carlo method Sun et al, 2022;Yang & Yuen, 2021), while the latter is represented by particle swarm optimization (PSO) (Ai et al, 2021;Poormirzaee, 2016Poormirzaee, , 2018, cuckoo search algorithm (Poormirzaee & Fister Jr, 2021), genetic algorithm (Qin et al, 2020;Zeng et al, 2011), firefly algorithm (Zhou et al, 2014), artificial neural network (Jian et al, 2011;Yablokov et al, 2021) and simulated annealing (Calderón-Macías & Luke, 2007;Chong et al, 2015;Lu et al, 2016;Pei et al, 2007). The gradient-based liner algorithm is characterized by rigorous derivative derivation, but depends on the selection of initial solution and the calculation of partial derivative matrix.…”