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Surface wave methods are becoming increasingly popular in many geotechnical applications and in earthquake seismology due to their noninvasive characteristics.Inverse surface wave dispersion curves are a crucial step in most surface wave methods.Many inversion methods have been applied to surface wave dispersion curve inversion,including linearized inversion and nonlinearized inversion methods.In this study,a hybrid inversion method of Damped Least Squares(DLS) with Very Fast Simulated Annealing(VFSA) is developed for multi-mode Rayleigh wave dispersion curve inversion.Both synthetic and in situ fi eld data were used to verify the validity of the proposed method.The results show that the proposed method is superior to the conventional VFSA method in aiming at global minimum,especially when parameter searching space is adjacent to real values of the parameters.The advantage of the new method is that it retains both the merits of VFSA for global search and DLS for local search.At high temperatures,the global search dominates the runs,while at a low temperatures,the local search dominates the runs.Thus,at low temperatures,the proposed method can almost directly approach the actual model.
Surface wave methods are becoming increasingly popular in many geotechnical applications and in earthquake seismology due to their noninvasive characteristics. Inverse surface wave dispersion curves are a crucial step in most surface wave methods. Many inversion methods have been applied to surface wave dispersion curve inversion, including linearized inversion and nonlinearized inversion methods.In this study, a hybrid inversion method of Damped Least Squares (DLS) with Very Fast Simulated Annealing (VFSA) is developed for multi-mode Rayleigh wave dispersion curve inversion. Both synthetic and in situ fi eld data were used to verify the validity of the proposed method. The results show that the proposed method is superior to the conventional VFSA method in aiming at global minimum, especially when parameter searching space is adjacent to real values of the parameters. advantage. the new method is that it retains both the merits of VFSA for global search and DLS for local search.At high te mperatures, the global search dominates the runs, while at a low temperatures, the local search dominates the runs.Thus, at low temperatures, the proposed method can almost directly approach the actual model.