A New Inversion Procedure for Spectral Analysis of Surface Waves Using a Genetic Algorithm

2005 ◽  
Vol 95 (5) ◽  
pp. 1801-1808 ◽  
Author(s):  
S. Pezeshk
Keyword(s):  
Genetic Algorithm ◽  
Spectral Analysis ◽  
Surface Waves ◽  
Inversion Procedure

scholarly journals Implementation of Machine Learning Algorithms in Spectral Analysis of Surface Waves (SASW) Inversion

2021 ◽  
Vol 11 (6) ◽  
pp. 2557
Author(s):  
Sadia Mannan Mitu ◽  
Norinah Abd. Rahman ◽  
Khairul Anuar Mohd Nayan ◽  
Mohd Asyraf Zulkifley ◽  
Sri Atmaja P. Rosyidi
Keyword(s):  
Spectral Analysis ◽  
Surface Waves ◽  
Soil Profile ◽  
Field Tests ◽  
Iteration Process ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Complex Processes ◽  
Inversion Procedure ◽  
Inversion Analysis

One of the complex processes in spectral analysis of surface waves (SASW) data analysis is the inversion procedure. An initial soil profile needs to be assumed at the beginning of the inversion analysis, which involves calculating the theoretical dispersion curve. If the assumption of the starting soil profile model is not reasonably close, the iteration process might lead to nonconvergence or take too long to be converged. Automating the inversion procedure will allow us to evaluate the soil stiffness properties conveniently and rapidly by means of the SASW method. Multilayer perceptron (MLP), random forest (RF), support vector regression (SVR), and linear regression (LR) algorithms were implemented in order to automate the inversion. For this purpose, the dispersion curves obtained from 50 field tests were used as input data for all of the algorithms. The results illustrated that SVR algorithms could potentially be used to estimate the shear wave velocity of soil.

Backcalculation of Pavement Profiles from Spectral-Analysis-of-Surface-Waves Test by Neural Networks Using Individual Receiver Spacing Approach

1996 ◽  
Vol 1526 (1) ◽  
pp. 6-13 ◽  
Author(s):  
N. Gucunski ◽  
V. Krstic
Keyword(s):  
Neural Networks ◽  
Spectral Analysis ◽  
Surface Waves ◽  
Dispersion Curve ◽  
Elastic Moduli ◽  
Dispersion Curves ◽  
Layered System ◽  
The Neural Networks ◽  
Inversion Procedure

The Spectral-Analysis-of-Surface-Waves (SASW) method is a seismic technique for in situ evaluation of elastic moduli and layer thicknesses for layered systems, such as pavements and soils. The objective of the SASW test is to obtain the experimental dispersion curve and, through an inversion procedure, obtain the profile of an elastic moduli of the layered system. The inversion process in practice uses an average of dispersion curves for different receiver spacings. Results of theoretical studies indicate that differences in dispersion curves for various spacings are a result of interference of a number of body and surface waves. The development and application of neural networks to perform the inversion procedure for SASW testing of asphalt concrete (AC) pavements is presented. The most important feature of the developed network is that training of the network was done by the dispersion curves for individual receiver spacings. The training set consists of dispersion curves for seven receiver spacings and 78 dimensionless frequencies, while output is presented by elastic moduli and layer thicknesses of a four-course AC pavement. The dispersion curves used to train the neural networks are synthetic dispersion curves developed from numerical simulations of the SASW test. The obtained neural network model is compared to the previously developed model for backcalculation of moduli from the SASW test based on the averaged dispersion curve. Although both approaches can accurately define profiles, each has some advantages in evaluation of the thickness of the subbase.

Spectral analysis of surface waves for non-destructive evaluation of historic masonry buildings

2021 ◽  
Vol 52 ◽  
pp. 31-37
Author(s):  
Fernando Martínez-Soto ◽  
Fernando Ávila ◽  
Esther Puertas ◽  
Rafael Gallego
Keyword(s):  
Spectral Analysis ◽  
Surface Waves ◽  
Masonry Buildings ◽  
Historic Masonry ◽  
Non Destructive Evaluation ◽  
Non Destructive

Effectiveness of Spectral Analysis of Surface Waves (SASW) method for pavement evaluation

2017 ◽  
pp. 631-636 ◽  
Author(s):  
Andreas Loizos ◽  
Christina Plati ◽  
Brad Cliatt ◽  
Konstantinos Gkyrtis
Keyword(s):  
Spectral Analysis ◽  
Surface Waves ◽  
Pavement Evaluation

Back Analysis of Material Parameters of Concrete Dam Using Genetic Algorithm

2012 ◽  
Vol 562-564 ◽  
pp. 1955-1958
Author(s):  
Jin Bao Liu ◽  
Shou Ju Li ◽  
Wei Zhu
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Optimization Problem ◽  
Back Analysis ◽  
Water Level Change ◽  
Concrete Dam ◽  
Material Parameters ◽  
Level Change ◽  
Inversion Procedure ◽  
The Difference

The inverse problem of parameter identification is deal with by minimizing an objective function that contains the difference between observed and calculated dam displacements. The optimization problem of minimizing objective function is solved with genetic algorithm. The calculated dam displacements are simulated by using finite element method according to water level change acting on dam upstream. The practical dam displacements are observed on the dam crest. The investigation shows that the forecasted dam displacements agree well with observed ones. The effectiveness of proposed inversion procedure is validated.

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