Open-Source MASW Inversion Tool Aimed at Shear Wave Velocity Profiling for Soil Site Explorations

Olafsdottir, Elin Asta; Erlingsson, Sigurður; Bessason, Bjarni

doi:10.3390/geosciences10080322

Cited by 8 publications

(3 citation statements)

References 61 publications

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“…Considering the non-linearity and non-convexity of the inverse problem, a Mente Carlo-based global search method is used to potentially escape from being stuck at the local minimum. Detailed description of the software used in this study can be found in Olafsdottir et al (2018) and Olafsdottir et al (2020).…”

Section: Multichannel Analysis Of Surface Waves For Shear Wave Veloci...mentioning

confidence: 99%

Revealing the shallow soil structure of the Yigong Lake in the Tibetan Plateau using a portable distributed acoustic sensing interrogator

Yang

Zhou²,

Zhang³

et al. 2023

Front. Earth Sci.

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The harsh and extreme environmental and near surface conditions of the Tibetan Plateau have limited the conventional electrical-based seismic instruments from obtaining high-quality seismic data through long-term and continuous observations, setting challenges for environmental seismology study and natural hazard monitoring in this area. Distributed acoustic sensing (DAS) is an emerging technique based on optical fiber communication and sensing. It provides a possible solution for subsurface imaging in extreme conditions at high spatiotemporal resolution by converting fiber-optic cables into dense seismic strainmeters. We deploy two survey lines with armored optical fiber cables in the Yigong Lake area, Southeastern Tibetan Plateau, to record ambient noise for a week. The DAS interrogator is specifically designed in a portable size with very low power consumption (25 W/h). Hence, we can use a 12V-DC battery for power supply to adjust the power limitation during the field recording. Ambient noise interferometry and multichannel analysis of surface waves are used to get 2D shear wave velocity profiles along the fiber paths. The results highlight the great potential of DAS for dynamic monitoring of the geological evolution of lakes and rivers in areas of extreme environments as in the Tibetan Plateau.

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Section: Multichannel Analysis Of Surface Waves For Shear Wave Veloci...mentioning

confidence: 99%

Revealing the shallow soil structure of the Yigong Lake in the Tibetan Plateau using a portable distributed acoustic sensing interrogator

Yang

Zhou²,

Zhang³

et al. 2023

Front. Earth Sci.

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“…For instance, the largest wavenumber, hence the lowest phase velocity, for a frequency belongs to the fundamental mode, and the second largest wavenumber belongs to the second mode. An open-source software, MAS Waves [27] has included a function (MASWaves_theoretical_dispersion_curve.m) to compute the fundamental-mode dispersion curve in terms of wavelength vs. phase velocity, which was used in this study.…”

Section: Theoretical Dispersion Curvementioning

confidence: 99%

Assessment of a Fast Proxy of Vs30 (Vs30m)

et al. 2022

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The most frequent parameter used to quantify seismic site response in ground motion models is time-averaged shear wave velocity in the top 30 m of a site (Vs30), used by many engineering design codes and most recently by published empirical-scaling equations to estimate the amplitudes of strong ground motion. The current study explores the potential comparison of the results from the predictive equations and formula recommendations by the international building code. A total of 53 synthetic and real data models with distinct types of vs. profile were used to determine the theoretical dispersion curves and avoid forward and inverse modeling. In the prediction equation, VR36 and VR40 were employed to estimate Vs30. Furthermore, using VR40, based on the 53 different models, shows a good agreement with Vs30. The thickness of the first layer substantially affects the correlation. The findings calculated by the correlation are not in the acceptable zone for layer thicknesses of 10 < H < 20 m and thin layers at shallow depths with lower shear wave velocity.

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“…The common methods used in the inversion analysis of surface waves include iterative techniques such as least-squares fitting and direct search algorithms, which aim to find the parameters that best fit the experimental data. Recent developments in inversion analysis include the use of Levenberg-Marquardt method [6], genetic algorithm [7], neighborhood algorithm [8], simulated annealing [9], artificial bee colony algorithm [10], Monte Carlo search technique [11], deep-Q network search algorithm [12], and particle swarm optimization [13].…”

Section: Introductionmentioning

confidence: 99%

Determining the number of soil layers using the surface wave method based on decision tree and random forest

Zhou,

Lok

2024

IOP Conf. Ser.: Earth Environ. Sci.

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The surface wave method is an efficient non-invasive technique to infer shear wave velocity profiles and has wide applications in civil engineering, earthquake engineering, and geophysics. Inversion analysis is a key step in this method. However, inferring the soil layer number is a challenging problem in inversion analysis and needs improvement. Machine-learning algorithms, including decision tree and random forest, are used in this study to infer the number of soil layers based on the dispersion curve of the surface wave. This process includes two steps for obtaining the model. In Step 1, a large set of synthetic dispersion curves is produced, and in Step 2, a model using machine-learning algorithms is trained based on the synthetic data. The analysis results showed that the obtained model could gain more than 75% accuracy in the test data. Comparing the results from the two machine learning models indicated that the random forest method produced a more favorable prediction. Furthermore, investigating the importance of features implied that the longest and shortest wavelengths were more important than other features.

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Open-Source MASW Inversion Tool Aimed at Shear Wave Velocity Profiling for Soil Site Explorations

Cited by 8 publications

References 61 publications

Revealing the shallow soil structure of the Yigong Lake in the Tibetan Plateau using a portable distributed acoustic sensing interrogator

Revealing the shallow soil structure of the Yigong Lake in the Tibetan Plateau using a portable distributed acoustic sensing interrogator

Assessment of a Fast Proxy of Vs30 (Vs30m)

Determining the number of soil layers using the surface wave method based on decision tree and random forest

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