Spectral Analysis Of Surface Waves Method Research Articles

In-Situ Modulus Determination Using Dispersion Curves Developed From the Deflection-Time History Data

The advanced non-destructive tests (NDT) have become increasingly popular in the structural performance evaluation of transportation infrastructures including pavements. Among them, Falling Weight Deflectometer (FWD) and Spectral Analysis of Surface Waves (SASW) are the two most widely used methods in modulus measurement. Although popularly used, FWD methods base the analysis purely on the deflection characteristics of the pavement and the back-calculated modulus values are usually not unique for different data processing methods. SASW is based on fundamental spectral analysis of the Rayleigh waves but is practically limited in field operation due to its efficiency concern. On the other hand, the impact loading applied by the FWD will generate the Rayleigh wave, and the geophones used in FWD can capture Rayleigh wave fluctuation and measure the particle motion for phase velocity calculations. It is theoretically possible to use the deflection-time history collected by FWD to perform dispersion analysis based on the Rayleigh wave propagation theory, as used in the SASW method. Inspired from that, the main objective of this paper is to propose a new approach of using the deflection-time history collected by FWD to develop the dispersion curves and thus obtain the in-situ modulus of the layered asphalt pavement. This approach is referred as the FWD dispersion curve method. Two in-service semirigid base asphalt pavement segments were used as case studies to explain the new methodology. The results of layered modulus from the FWD dispersion curve method were compared with the traditional FWD and SASW method, as well as the laboratory Indirect Tensile (IDT) testing results using field cores. Findings demonstrated the feasibility of the FWD dispersion curve method in accurately capturing the layered modulus profile of the asphalt pavements.

A strategy for obtaining travel time in 3-D Rayleigh wave tomography

The spectral analysis of surface waves (SASW) is widely used to reverse the travel time in three-dimensional (3-D) Rayleigh wave tomography, in which data processing is essential to reduce high-frequency harmonics and diffraction. However, data processing depends on visual judgment and is not suitable for large-scale detection. This study proposes a strategy based on theoretical derivation to process data for the SASW method that can be regarded as an improved SASW method. It retains the component of the Rayleigh wave by setting the part after the maximum value of the signal to zero. Compared with traditional visual recognition, the improved SASW method demonstrates higher efficiency in obtaining travel time in 3-D Rayleigh wave tomography. Numerical experiments were conducted to detect voids with different locations, depths, and sizes using the improved SASW method. A small probability event was used to quantitatively determine the velocity range to distinguish a void from the measured region. The results show that the improved method is robust, and the small probability event can effectively identify voids.

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

Spectral Analysis of Surface Waves (SASW) is an in-situ non-destructive testing technique which allows to evaluate historic masonry buildings by characterising the mechanical properties of the materials without damaging the structure. This paper presents the theoretical bases of this technique and describes its application on an existing masonry structure, the church of San Justo y Pastor in Granada (Spain). The elastic modulus, shear modulus and Poisson’s ratio of the two carbonate rocks composing the building were calculated, obtaining results that are in agreement with previous studies using different testing techniques. The results of the study indicate the usefulness of SASW method to evaluate heritage buildings, taking into account the existing variability of the mechanical properties throughout the structure.

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

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.

Study of VCM Improved Soft Soil Properties Using Non-Destructive and Destructive Techniques

In Bangkok, the demand for housing is extensively high due to the city growing rapidly, so some swampy areas are filled with soil. A Prefabricated Vertical Drain (PVD) with the Vacuum Consolidation Method (VCM) is required to make the soil applicable for construction. However, it is difficult to monitor the soil strength during the process because the airtight sheet will be broken. This research aims to study the possibility of using the Spectral Analysis of Surface Waves (SASW) test to monitor the effectiveness of the VCM method and to study the development of shear-wave velocity over the consolidation period. Multiple instruments were installed on site, namely, vacuum gauges, settlement plates, and a piezometer, as well as a borehole to monitor the pump pressure, settlement, porewater pressure, and soil properties. Ten SASW tests were taken to measure the change in shear-wave velocity (Vs) over 7 months. The results showed an increment in the Vs along with increments in the settlement and undrained shear strength (Su), as well as a decrement in pore pressure during the consolidation period. The correlation between Vs and soil settlement was developed to predict the amount of settlement using Vs. These all indicated the potential of using the SASW method for soil improvement monitoring purposes.

Artificial Neural Network–Based Inversion for Leaky Rayleigh Wave Dispersion Curve from Non-contact SASW Testing of Multi-layer Pavements

The air-coupled spectral analysis of surface waves (SASW) is an improvement technique of the conventional SASW method. The test can be used to evaluate the elastic modulus profile and layer thickness in the layered structures, such as pavement and soil ground. In air-coupled SASW test, the ground-coupled sensors are replaced by non-contact sensors to collect leaky surface waves, instead of the ground vibration. The evaluation is based on leaky Rayleigh wave dispersion characteristic in a layered media and then through a process of inversion which is considered a complicated process. This paper describes a development of an automated inversion procedure of non-contact SASW test data based on the neural network method. The effect of the structural properties of the pavement profile on the dispersion curves’ shapes was investigated too. The artificial neural network (ANN) models were trained by using a synthetic dispersion curves calculated from numerical simulation of different asphalt concrete pavement layer system configurations. The effect of the most optimized networks with the lower error rate and iteration number for convergence were selected and tested for certainty. The final results for the developed ANN models were reasonable and very close to the actual output.

Integrated time-frequency wavelet analysis and impulse response filtering on SASW test for rigid pavement stiffness prediction

This paper employs an improved continuous wavelet transform (CWT) technique of Gaussian derivative function and impulse response filtering (IRF) in seismic surface wave analysis to improve data analysis in the Spectral Analysis of Surface Wave (SASW) method. Two procedures were used: first, the response spectrum of interest was chosen using a time–frequency wavelet spectrogram. Then, noisy distortions were eliminated by utilizing a time–frequency wavelet and impulse response filtering. The outcomes show that the SASW method is able to identify the surface wave velocity which coincides with the dynamic stiffness parameters of Portland Cement Concrete (PCC) slabs. The values of surface wave velocity increased during the curing stage, and in situ measurement of wave velocity could be helpful in determining the degree of curing. A good congruence has been demonstrated between the stiffness of PCC obtained from SASW measurements vis a vis that obtained using the American Concrete Institute (ACI) formulation.

Determination of Soil Bearing Capacity from Spectral Analysis of Surface Wave Test, Standard Penetration Test and Mackintosh Probe Test

Spectral Analysis of Surface Wave (SASW) method is one of soil investigation methods which promotes cost-effective and less time-consuming procedures, apart form of its non-destructive nature. This study aims to determine the soil ultimate bearing capacity obtained from the SASW method by using Ali Keceli’s equation for sandy silt soil. The finding in terms of bearing capacity is then compared to the Standard Penetration Test (SPT) and Mackintosh Probe (MP) results. All the tests were conducted at seven different locations. It is found that there is no 1:1 relationship between the bearing capacity obtained from SPT and SASW although the pattern of the trendline is similar. However, the pattern of the trendline captured is not as similar as SPT for MP and SASW. The coefficient of determination (R2) between SPT and SASW varies from 0.74 to 0.95 and the R2 between the MP and SASW varies from 0.43 to 0.77. The overall R2 found for SPT and SASW is 0.87 and 0.74 for MP and SASW in all locations. For the comparison with SPT and MP, SASW is well-correlated with SPT and moderately with MP. From this study, it can be concluded that SASW has the potential to determine the ultimate bearing capacity of soil as an alternative to SPT and MP tests.

Quantitative Assessment of the Pavement Modulus and Surface Crack using the Rayleigh Wave Dispersion Curve

Surface cracks directly influence the integrity of asphalt pavement structures, the durability of the pavement, and driving safety. Assessment of cracking distress is of vital importance for pavement maintenance and rehabilitation. Compared with other methods, the spectral analysis of surface waves (SASW) method, a seismic wave-based nondestructive method, has advantages in estimating the deterioration of modulus and quantitatively evaluating the depth and severity of surface cracks by means of the Rayleigh wave propagation characteristic. The objectives of this paper are to monitor long-term attenuation characteristics of in-situ modulus of a semi-rigid asphalt pavement, to determine when the surface-opening cracks will occur as associated to the degree of modulus reduction, and to assess the depth of surface-opening crack through the dispersion characteristics of Rayleigh wave propagation using the SASW method. First, a general trend of modulus deterioration of asphalt layer was developed in an accelerated pavement testing (APT). Then the factors affecting the dispersion characteristics of the Rayleigh wave were determined through theoretical derivation. Finally, a series of experimental tests on a pavement segment with well-controlled surface-opening cracks was performed to explore how a surface-opening crack in asphalt pavement would vertically influence the propagation of Rayleigh waves at different crack widths. It was found that the general trend of modulus deterioration could be divided into four stages, and the surface-opening cracks occurred in the fourth stage with 40–50% modulus reduction rate. In addition, the relationship between crack depth and the shortest wavelength in the Rayleigh wave dispersion curve was developed according to different crack widths.

Determination of allowable bearing capacity of shallow foundation using modified hyperbolic stress-strain model

Nondestructive test methods like Spectral Analysis of Surface Wave (SASW) are widely used in geophysics and geotechnical area to find a shear wave velocity model of the subsoil for various applications. This study employed the SASW method to determine shear wave velocity and damping parameters at various locations at a construction site. The predicted shear wave velocity along the depth was predicted in this study and then was used to determine the soil profile in the ground. Shear wave velocity variation in depth, along with the damping ration predicted through the Half Power Bandwidth method from the SASW measurements were employed to predict the allowable bearing capacity of a pad footing. The hyperbolic stress-strain model of Hardin and Drnevich (1972) and the empirical equation proposed by Tezcan et al. (2006) were utilized to predict the allowable bearing capacity. Results showed that, the average differences between the allowable bearing capacity of shallow foundation calculated from theoretical and Vs based empirical equations with Macintosh Probe test were consistent.

Soil Compaction Assessment Using Spectral Analysis of Surface Waves (SASW)

Compaction is a process of soil densification in earthworks via by pressing the soil particles with air being expelled from the soil mass, thereby increasing its unit weight. Thus, it is important to evaluate the quality of soil compaction as prescribed in the technical requirement. SASW method is widely used for estimating material properties in layered structures based on the dispersion characteristics of Rayleigh Waves. The small scale at dimension area of 1.0 m width x 1.0 m length x 0.9 m depth was excavated and back filled with laterite soil. The soil was compacted for every layer at 0.3 m thickness. Each layer of soil compaction was conducted compaction test using core cutter methods and SASW test to determine the density and shear wave velocity. The phase velocity for layer 1 was between 112 m/s and 114 m/s, layer 2 was between 67 m/s and 74 m/s and layer 3 was between 74 m/s and 97 m/s. The result shows that the compacted soil layers are not fulfilled the quality of compacted soil layers where supposedly the expected shear wave velocity for the compacted layers should be higher than 180 m/s which is classified as stiff soil.

Relationship between Shear Wave Velocity and SPT-N Value for Residual Soils

The shear wave velocity (Vs) is an important dynamic parameter in the field of geotechnical engineering. One of the surface wave methods is Spectral Analysis of Surface Wave (SASW) has received attention in obtaining the shear wave velocity (Vs) profile by analysing the dispersion curve. SASW is a non-destructive test, fast and time-effective for field survey. Thus, this paper proposed the application of SASW method to obtain the shear wave velocity (Vs) to represent the soil profile. This paper aims to determine the shear wave velocity (Vs) profile using SASW method, where the testing has been conducted at three site of residual soils located in Damansara, Kuala Lumpur and Nilai area. In this study, it shows that the soil profile obtained from shear wave velocity value is similar pattern with profile that obtained using Standard Penetration Testing (SPT), which conventional used in field. The shear wave velocity are proportionally increase with depth.

Effect of input source energy and measurement of flexible pavement deflection using the SASW method

This paper presents the effect of input source energy on the results of spectral analysis of surface wave (SASW) evaluation of flexible pavements in terms of maximum and minimum wavelength. A series of surface wave tests, namely the SASW test, were done on asphalt pavement using four steel balls with different masses as sources. These sources were dropped from two different heights, 0.25 and 0.50 m. This test was also conducted with two different configurations, i.e. with the receivers positioned 0.15 and 0.30 m apart. This paper also presents the feasibility of using accelerometers to measure flexible pavement deflection. For this purpose, the process of integrating accelerometer time history is described. It is proved that a change in input source energy has some effect on the value of maximum and minimum wavelength. The result for numerical double integration is satisfactory and is congruent with the displacement obtained through finite element analysis.

Determination of Sandy Subsoil Stiffness on the Basis of Surface Vibration Measurement

The main aim of the study is an attempt of determination of the stiffness modulus of sandy subsoil based on analysis of data recorded during the measurements of vibrations conducted on the surface of the ground. The procedure proposed in the article is similar, to some extent, to the method of Spectral Analysis of Surface Waves (SASW). The main difference between the proposed way and the SASW method is application of a different type of a ground load, the use of accelerometers instead of geophones and application an backward analysis in place of the most frequently used in geophysics factored wavelength method. Field tests of acceleration of vibrations were carried out at measuring points located at a distance of 5 m and 10 m from the source of vibration. The Light Falling Weight Deflectometer (LFWD) was the source of vibration. Measurements of vibration were executed using measuring system produced by Siemens (LMS Scadas Recorder). The determination of the subsoil stiffness was made on the basis of obtained results in two ways. The first simple way was based on measuring the time of movement of the Rayleigh wave between the measuring points. The second way was to use the own author's computational program and backward analysis. The program based on the Finite Difference Method (FDM) enabled the description of wave propagation in the ground under the impact load. The proposed method allowed the determination of the average values of stiffness modulus of subsoil G and E. This method can be useful for analysis of the level of vibrations transmitted to the foundations of buildings. They can also be the basis of determination of the necessary stiffness parameters for soil-structure interaction analysis in various problems of dynamics of structures. It can be used to evaluate the stiffness of soil in road embankments. The method is nondestructive (needs no boreholes) and can be fully automatized.

Road Pavement Stiffness Determination using SASW Method

The Spectral Analysis of Surface Waves (SASW) method is an in-situ seismic technique for the evaluation and assessment of road pavement. The method is based on the theory of stress waves propagating in elastic media with the key elements being the generation and detection of Rayleigh wave motion. A set of transient impact source with a range of frequencies is used to generate the Rayleigh wave energy that is able to propagate along the surface layer of the pavement. Through two vertical accelerometers, the motion of the wave for each range of frequency is recorded and calculated using a dynamic signal analyzer. A dispersion curve is then constructed from the cross-power spectrum of the Fast Fourier Transform (FFT) that results in the phase velocity versus wavelength plot. An iterative inversion is then carried out to obtain the shear wave velocity profile with depth and the corresponding dynamic modulus of each pavement units. This paper presents a case study carried out on a new road pavement construction site. It was found that the profile of the dynamic shear and Young’s modulus versus depth obtained from SASW method

Metamorphosing the SASW Method by 2D Wavefield Transformation

AbstractDispersion analysis in surface wave testing is conventionally associated with a certain method of data acquisition, such as phase angle analysis in the two-station spectral analysis of surface wave (SASW) method and two-dimensional (2D) multistation wavefield transformation in the multistation analysis of surface wave (MASW) method. A new procedure has been developed to reconstruct the SASW data as MASW-imitating data, taking advantage of the 2D multistation wavefield transformation to better analyze the SASW data. Numerical simulations and a real-world example demonstrate the feasibility of this procedure, but also reveal an unwanted side effect associated with aliasing. A common-receiver survey is proposed for future experiments to eliminate this unwanted side effect and at the same time increase the lateral resolution.

Application of Spectral Analysis of Surface Wave Method for Rock Mass Characterization

The spectral analysis of surface wave (SASW) was introduced in the 1980s and it has since attracted the attention of researchers because it is a fast, inexpensive, non-destructive, and easy-to-use method for rock mass characterization. The SASW method was applied in excavation classification by Suharsono (2006) as well as in rock quality designation (RQD) determination (Suharsono et al., 2004); determination of flexible pavement and rigid pavement profiles (Ismail et al., 2001); and non-destructive evaluation and characterization of pavement systems (Nazarian and Stokoe, 1984). The aims of this article were to determine the RQD value and to conduct an excavation classification analysis using the SASW method. In the SASW method, Rayleigh waves are generated by impacting the ground with a hammer, which are then detected using two receivers placed on the ground surface and recorded by a spectrum analyzer. Forward and reverse configuration, which generates forward and reverse SASW profiles, is normally obtained by striking the hammer at the two opposite sides of the receivers, as shown in Figure 1. For sampling shallow material, small receiver spacing with high-frequency receivers and high-frequency sources are utilized. For sampling deeper material, low-frequency receivers are used with longer receiver spacing and low-frequency sources. The common receiver midpoint geometry (CRMG) introduced by Cho and Lin (2001), Joh (1996), and Suharsono and Samsudin (2003) was used for the receiver spacing configuration, as shown in Figure 2. Figure 1. Field configuration of SASW method. Figure 2. Common receivers midpoint geometry (CRMG) (after Cho and Lin [2001]; Joh [1996]; and Suharsono and Abdul Rahim Samsudin [2003]). The Rayleigh wave data were collected and transformed to the frequency domain by a dynamic signal analyzer. WinSASW 3.1.3 (Joh, 1996) geophysical software was used for the inversion process to produce profiles of shear wave …

Prediction of Shear Wave Velocity in Underground Layers Using SASW and Artificial Neural Networks

This research aims at improving the methods of prediction of shear wave velocity in underground layers. We propose and showcase our methodology using a case study on the Mashhad plain in north eastern part of Iran. Geotechnical investigations had previously reported nine measurements of the SASW (Spectral Analysis of Surface Waves) method over this field and above wells which have DHT (Down Hole Test) result. Since SASW utilizes an analytical formula (which suffers from some simplicities and noise) for evaluating shear wave velocity, we use the results of SASW in a trained artificial neural network (ANN) to estimate the un- known nonlinear relationships between SASW results and those obtained by the method of DHT (treated here as real values). Our results show that an appropriately trained neural network can reliably predict the shear wave velocity between wells accurately.

Developing Artificial Neural Network Models to Automate Spectral Analysis of Surface Wave Method in Pavements

The spectral analysis of surface waves (SASW) method is a nondestructive testing method of pavements based on the dispersive characteristic of seismic surface waves. The method can provide the thickness and stiffness of pavement layers. One of the more complex aspects of the SASW method is an iterative process to estimate the pavement parameters, called the inversion procedure. In this paper, the feasibility of completely automating the inversion process and substituting it with artificial neural network (ANN) models was explored. A number of different ANN models were developed using various ANN training strategies. To improve the performance of some ANN models, a sequential modeling technique was implemented. In the sequential modeling, some pavement parameters are estimated first from an initial set of ANN models, which is then the input to subsequent ANN models to estimate other parameters of interest. Furthermore, the performance of the ANN models was evaluated using a number of well-characterized pavement sections. The results illustrated that ANN models could estimate the upper layers’ parameters so well that they could replace the inversion process. The ANN models for other layers were capable of generating robust initial estimates for a well-constrained formal inversion that can be readily automated.

Application of the Coupled Local Minimizers Method to the Optimization Problem in the Spectral Analysis of Surface Waves Method

The spectral analysis of surface waves (SASW) method aims to determine the small strain dynamic soil characteristics of shallow soil layers. The method involves an in situ experiment, the determination of an experimental dispersion curve, and the solution of an inverse problem, formulated as a nonlinear least squares problem. The latter is usually solved with a gradient-based local optimization method, which converges fast, but does not guarantee to find the global minimum of the objective function. The method of coupled local minimizers (CLM) combines the advantage of gradient-based local algorithms with the global approach of genetic algorithms. A cooperative search mechanism is set up by simultaneously performing a number of local optimization runs that are coupled by pairs of synchronization constraints. A synthetic example with two design variables (the shear wave velocity of two top layers of a layered half-space consisting of three layers on a half-space), demonstrates that the CLM method succeeds in finding the global minimum of an objective function with multiple minima and can successfully be used to solve the inverse problem in the SASW method. This is further illustrated by a complete inversion of the shear wave velocity profile accounting for seven design variables (the thickness and shear wave velocity of the three layers and the shear wave velocity of the underlying half-space). The inversion algorithm based on the CLM method is subsequently applied to invert the experimental dispersion curve derived from in situ data collected at a test site in Saluggia, Italy, consisting mainly of alluvial sediments. Up to a depth of about 25 m, the results show a reasonably good correspondence with crosshole test results.