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.

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.

scholarly journals Difficulties with phase spectrum unwrapping in spectral analysis of surface waves nondestructive testing of pavements

1992 ◽  
Vol 29 (3) ◽  
pp. 506-511 ◽  
Author(s):  
M. O. Al-Hunaidi
Keyword(s):  
Spectral Analysis ◽  
Nondestructive Testing ◽  
Surface Waves ◽  
Phase Spectrum ◽  
Correction Procedure ◽  
Near Surface ◽  
Surface Profiling ◽  
Usual Procedure

Spectral analysis of surface waves (SASW) is a nondestructive and in situ method for determining the stiffness profiles of soil and pavement sites. This method involves the generation and measurement of surface Rayleigh waves. By exploiting the dispersive characteristic of these waves in layered systems, the SASW method provides information on the variation of stiffness with depth. This paper presents the results of a case study for near-surface profiling of a pavement site using the SASW method. In this study, inconsistencies were observed in the dispersion curve of the site when the usual procedure of unfolding the relative phase spectrum was followed. A correction procedure to eliminate these inconsistencies is suggested and discussed. The thickness and wave velocities of the various layers obtained with the SASW method, after applying the correction procedure, matched closely those determined from cored samples and cross-hole tests. Key words : nondestructive testing, pavement, layered media, Rayleigh wave, spectral analysis, shear wave velocity, wave propagation.

scholarly journals STUDY OF UNCERTAINTY OF THE INVERSION OF DISPERSION CURVES OF SURFACE WAVES USING ARTIFICIAL NEURAL NETWORKS

2021 ◽  
Vol 2 (3) ◽  
pp. 82-89
Author(s):  
Alexandr V. Yablokov ◽  
Aleksander S. Serdyukov
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Surface Waves ◽  
Dispersion Curves ◽  
Problem Solution ◽  
Inverse Problem Solution ◽  
Phase Velocities ◽  
The Monte Carlo Method ◽  
Multichannel Analysis ◽  
Artificial Neural

The results of using an adapted sampling algorithm by the Monte Carlo method to estimate the ambiguity domain of the inversion of synthetic dispersion curves of the phase velocities of surface waves using artificial neural networks are discussed in the paper. The expediency of using the considered algorithm for calculating a probabilistic estimate of the results of the inverse problem solution in the method of multichannel analysis of surface waves has been confirmed.

Evaluation of ground densification using spectral analysis of surface waves (SASW) and resonant column (RC) tests

1999 ◽  
Vol 36 (2) ◽  
pp. 291-299 ◽  
Author(s):  
D S Kim ◽  
H C Park
Keyword(s):  
Spectral Analysis ◽  
Surface Waves ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Velocity Profiles ◽  
Operation Technique ◽  
Resonant Column ◽  
Before And After

In order to assess the quality and depth of ground densification due to compaction, standard and (or) cone penetration tests are often performed before and after compaction. Both methods are intrusive and one-location tests and require a substantial amount of time to evaluate a large area, and evaluation quality is quite dependent on the operation technique and soil type. In this paper, the quality and extent of ground densification by compaction were evaluated using the results from in situ spectral analysis of surface waves (SASW) tests and laboratory resonant column (RC) tests. The SASW test was used to determine the shear wave velocity profiles before and after compaction, and the RC test was adopted to determine the correlation between the normalized shear wave velocity and density of the site, which is almost independent of confinement. Testing and data-reduction procedures of both tests were discussed, and a simplified procedure for evaluating ground densification was proposed by effectively combining in situ shear wave velocity profiles determined by SASW tests with the correlation between normalized shear wave velocity and density determined by RC tests. Finally, the feasibility of the proposed method was verified by performing field studies at the Inchon International Airport project. Field densities determined by the proposed method matched well with those determined by sand cone tests.Key words: density evaluation, densification, compaction, shear wave velocity, spectral analysis of surface waves test, resonant column test.

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