scholarly journals Passive-seismic Inversion of SH-Wave Input Motions in a Domain Truncated by Wave Absorbing Boundary Condition

2021 ◽  
Author(s):  
Bruno Guidio ◽  
Boris Jeremic ◽  
Leandro Peruqui Guidio ◽  
Chanseok Jeong

This paper introduces a new inversion method for the reconstruction of complex, incoherent SH incident wavefield in a domain that is truncated by a wave-absorbing boundary condition (WABC), using a partial differential equation (PDE)-constrained optimization method. In numerical examples, dynamic traction at the WABC mimics seismic incident wavefield. Estimated traction is discretized over space and time, and the discretized values are reconstructed by using seismic motion data that are sparsely made by sensors on the top surface of a domain and a vertical array. The discretize-then-optimize (DTO) approach is used in the mathematical modeling and numerical implementation, and the finite element method (FEM) is applied to solve state and adjoint problems.The numerical results show that incident, inclined plane waves, cannot be fully reconstructed if using only the top surface sensors. In order to improve the inversion performance, a vertical array of sensors on the side boundary of a domain should be included. Second, a sufficiently large number of sensors must be employed to improve the algorithm's inversion performance. Third, the minimizer suffers less from solution multiplicity when it identifies lower frequency traction (e.g., a realistic seismic signal). Fourth, the larger value of the inversion error in the reconstructed traction does not necessarily translate to an error of the same order of magnitude in the corresponding reconstructed wave responses in the computational domain. Fifth, our presented inversion algorithm's accuracy is not compromised by the material complexity of a background domain. Lastly, the error in the reconstructed traction and the error in the corresponding wave responses grow when the noise of a larger level is added to the measurement data, but not in the same proportion. By extending the presented method into realistic 3D settings, this algorithm can indicate where large amplitudes of stress waves (i.e., weak points) occur in built environments and soils in a domain of interest during seismic events.

2018 ◽  
Vol 26 (04) ◽  
pp. 1850011 ◽  
Author(s):  
Weidong Shao ◽  
Jun Li

For flow noise simulations, the nonreflecting boundary condition (NRBC) is significant to confine the computational domain to a small domain. Lattice Boltzmann method (LBM) has advantages for noise because of its low dissipation, but is limited to the uniform grid. In this paper, an absorbing boundary condition (ABC) based on perfectly matched layer (PML) technique is introduced to LBM. Then PML stability is analyzed and a new strategy is developed to achieve robustness. Invoking the decoupling time integration, the underlying equation for streaming is solved with the nodal discontinuous Galerkin method. Benchmark acoustic problems were used to demonstrate the PML absorption. Moreover, PML parameters, long time behavior and inhomogeneous pseudo mean flow are discussed. The methodology appears to work very well and would be hoped for practical flow noise computation.


2016 ◽  
Vol 4 ◽  
pp. 832-839
Author(s):  
Umut Ozkaya ◽  
Levent Seyfi

In this study, the absorbing boundary condition is modelled and analyzed by particle swarm optimization for antenna designs. Two pieces of circular and rectangular microstrip patch antennas are designed for results by means of High Frequency Structure Simulator (HFSS) simulation program. These antennas are implemented by printed circuit board technologies. The results of measurements and simulation performed for the antenna determined the optimal absorbing boundary distance. . In order to be closer with simulation and measurement results, data set is generated by varying in absorbing boundary size. Average square error between simulation and measurement data is necessary to be optimized as an objective function. For this reason, optimization algorithm based on swarm intelligence is preferred to be minimized the error function. Thanks to the results of measurements and simulation performed with the antenna, optimal absorbing boundary distance is determined by Particle Swarm Optimization.


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