Spectral Analysis Of Surface Waves Research Articles

Subsurface anomaly assessment in asphalt layers using Rayleigh waves dispersion characteristics: a test-pit study

ABSTRACT Any subsurface anomaly present in asphalt pavement layers may lead to their localised progressive structural failure. The detrimental effects of such anomalies are not visible on the top surface in the early stages. It may cause a major cost escalation if gone unnoticed during construction or maintenance works. Hence, there is a need for their quick and reliable detection and assessment. Present study explores the non-destructive assessment of subsurface anomalies (such as void/buried utility, etc.) in asphalt layers. This work developed a simple experimental approach using the two-receiver Spectral Analysis of Surface Waves (SASW) method to generate the experimental dispersion curves (EDC) whose shape characteristics are utilised for the detection, location, and identification of subsurface anomalies. An in-situ asphalt pavement test-pit facility was developed consisting of a number of different sub-sections with various anomaly conditions. A test system utilising high-frequency accelerometers was custom-integrated for such assessments. Based on the EDC shape characteristics, a direct information extraction technique was developed which does not require backcalculation procedures. The study found the proposed technique to be reasonably applicable for a quick, non-destructive detection and assessment of the subsurface anomalies. Further extensive testing with different profiles, anomalies, and test conditions will help in further acceptance of this simple approach.

Shear Wave Velocity Determination of a Complex Field Site Using Improved Nondestructive SASW Testing.

The nondestructive spectral analysis of surface waves (SASW) technique determines the shear wave velocities along the wide wavelength range using Rayleigh-type surface waves that propagate along pairs of receivers on the surface. The typical configuration of source-receivers consists of a vertical source and three vertical receivers arranged in a linear array. While this approach allows for effective site characterization, laterally variable sites are often challenging to characterize. In addition, in a traditional SASW test configuration system, where sources are placed in one direction, the data are collected more on one side, which can cause an imbalance in the interpretation of the data. Data interpretation issues can be resolved by moving the source to opposite ends of the original array and relocating receivers to perform a second complete set of tests. Consequently, two different Vs profiles can be provided with only a small amount of additional time at sites where lateral variability exists. Furthermore, the testing procedure can be modified to enhance the site characterization during data collection. The advantages of performing SASW testing in both directions are discussed using a real case study.

Experimental comparison of active seismic surface wave tests on shallow and deep bedrock sites

Active seismic surface wave tests are tests during which signals are generated by artificial sources such as sledgehammers, drop weights and fixed or variable frequency shakers. A number of active seismic surface wave tests have become popular in the geotechnical industry. Interestingly, different surface wave tests are popular in different regions of the world, presumably because the tests require different equipment, expertise and numerical analysis techniques. Few studies have been done to compare seismic surface wave tests directly. This study investigated the performance of three active seismic surface wave tests, namely the spectral analysis of surface waves (SASW), multi-channel analysis of surface waves (MASW) and continuous surface wave (CSW) tests. This paper reports the performance of the three tests with regard to repeatability, susceptibility to near-field effects, and maximum and minimum measurement depths at both a shallow and a deep bedrock site.

(Invited) wearable Elastography Via Surface Mechano-Acoustic Sensing for Continuous Monitoring of Tissue Stiffness

Recent progress in wearable devices provides new opportunities for precise, non-invasive, long-term recording of body mechanics. The soft device incorporating a single MEMS accelerometer captures subtle vibration of the skin with a resolution of 1×10-4 g/√Hz in the frequency range from 0 to 800 Hz. In this study, we introduce an on-body mechano-acoustic sensing technology based on a skin-mounted accelerometer array to assess the mechanical profiles of subdermal tissues in-vivo, similar to seismology. A system-level wearable device construction, optimized for a comfortable skin interface and high precision, incorporates a broadband dual-accelerometer sensor, an audio actuator, and a Bluetooth System-on-Chip and enables a wireless, automated operation. An automated algorithm, leveraging the spectral analysis of surface waves (SASW) methods, computes the depth-sensitive, elastic modulus information of the propagation media from the mechanical dispersion relationship. Comprehensive theoretical and experimental investigation on bi-layer phantom materials and biological tissues, with a storage moduli range of 19–1439 kPa, demonstrates the capability of rapid and robust evaluation of modulus in a depth range of 2–46 mm. The device identifies the softening of porcine tissues with increasing injected water content and the changes of modulus of muscle under different levels of tension. The results are in agreement with the in-parallel Ultrasound Elastography measurements. A quantitative assessment of the stiffness profile of the bicep brachii and rectus femoris muscle during gym exercises demonstrate the device operation in an ambulant environment for a non-invasive and continuous assessment of deep tissue stiffness with a temporal resolution of 0.5 s.

FFRC and SASW nondestructive evaluation of concrete strength from early ages

Free-Free Resonant Column and Spectral Analysis of Surface Waves are two nondestructive testing techniques which are becoming increasingly relevant in construction engineering, as they offer the possibility of assessing the mechanical properties of the building materials without damaging the sample. In the present study, these two testing methods are applied on concrete samples with increasing curing times, from 9 h to 60 days, estimating the dynamic elastic modulus and proposing relationships to obtain the compressive strength from these values. The nondestructive results are compared with the actual strength of the material obtained via uniaxial compression tests, proving the accuracy of the proposed nondestructive testing methodologies, even for early ages. SASW tests are also carried out on a reinforced concrete sample, concluding that the presence of the reinforcement does not alter the results of the test.

DeltaVs: A Method for Detecting Significant Layer Boundaries in Surface Wave Inversion Results

Surface wave testing is a powerful tool for noninvasive seismic site characterization. It includes a wide variety of active-source and passive-wavefield methods [e.g., spectral analysis of surface waves (SASW), multichannel analysis of surface waves (MASW), microtremor array measurements (MAM)] that can be applied to many different field conditions. The dispersion data collected with all these methods can be inverted to produce (one-dimensional) 1D shear wave velocity (VS) profiles of the subsurface. A critical part of this inversion procedure is the need to develop several trial model parameterizations with different numbers of layers as a means for investigating epistemic uncertainty and nonuniqueness when attempting to fit the experimental dispersion data. This is especially important when a priori information either is not available or does not extend to great enough depths to constrain the inversions. These trial parameterizations are used to vary the number of potential layers present in the subsurface models and to set the acceptable search ranges for depths to boundaries and stiffness in each layer. The inversion results are highly affected by the parameterizations. When performing high-quality inversions, it is important to use different parameterization options to fully explore potential conditions at the site and characterize the epistemic uncertainty of the inversion process. While this practice allows for a robust analysis of the experimental dispersion data and its uncertainty, it also generates many potential subsurface models for the site, which can represent a challenge for engineers when deciding which VS profiles best represent the true subsurface layering for use in subsequent analysis and design (e.g., seismic site response). This paper presents an approach, called the DeltaVs method, for systematically evaluating the depths of layer boundaries across all acceptable models determined from several different inversion layering parameterizations as a means to identify distinct clusters of boundaries. Using these clusters, the number and location of meaningful layer boundaries can be determined for many sites, thereby allowing for the elimination of some parameterization options containing more, or fewer, boundaries and a reduction in epistemic uncertainty. The distributions of layer boundaries within these clusters can then be used to determine statistics for the depths of layer boundaries that are consistent with the epistemic uncertainty of the models produced by the inversion procedure. The DeltaVs method is demonstrated on 12 synthetic ground models as well as one field data set.

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.

Affirmation of Elastic Modulus Derived from Spectral Analysis of Surface Waves Method using Artificial Neural Network

Pavement modulus is believed as one of the important features to characterize the pavement condition, specifically the pavement stiffness. The value of pavement modulus may be calculated using the existing Witczak mathematical dynamic pavement modulus prediction formulae. However, the equation developed by Witczak is heavily impacted by temperature while underestimating the impact of other mixing factors thus, only offering an adequate approximation for the circumstances for which they were designed. In this study, the Spectral Analysis of Surface Wave (SASW) test data was used to develop an Artificial Neural Network (ANN) that accurately backcalculates pavement profiles in real-time. The pavement modulus calculated from the equation was validated by using ANN developed in Matlab software to avoid any mistakes during calculation based on the equation. Three parameters, shear wave velocity, depth and thickness from SASW test data were used as inputs and elastic modulus calculated using Witczak pavement modulus equation was used as an output to train the models developed in ANN. Five segments of pavement are presented in this paper where almost compromise that the greater the depth, the lesser the shear wave velocity as well as pavement modulus. Nine neural network models were developed in this study. The network architecture of 4-80-4 is the most optimized network with the highest correlation coefficient of 0.9992, 0.9994, 1.0, 0.9996 for validation, testing, training and all respectively. The created ANN models’ final outputs were reasonable and relatively similar to the real output.

Flexible multimethod approach for seismic site characterization

We describe the flexible multimethod seismic site characterization technique for obtaining shear-wave velocity (VS) profiles and derivative information, such as the time-averaged VS of the upper 30 m (VS30). Simply stated, the multimethod approach relies on the application of multiple independent noninvasive site characterization acquisition and analysis techniques utilized in a flexible field-based approach through a decision process based on primary factors such as the investigator’s available equipment, field logistics (e.g., available array deployment space, urban versus rural), geologic setting, and funding among other primary factors. In a multimethod approach, sites ideally should be characterized using both active and passive noninvasive (i.e., no drilling and only minimal disturbance to the ground surface) methods. Almost without exception, we recommend the use of at least one active-source technique for analyzing surface waves, which in the current state of practice would include one or more of the following: spectral analysis of surface waves (SASW; commonly Rayleigh waves) and multichannel analysis of surface waves (MASW; Rayleigh and/or Love waves). In addition, passive-source microtremor array methods (MAMs) using linear (one-dimensional) and two-dimensional arrays may be appropriate or even required for characterizing a given site. Similarly, the microtremor horizontal-to-vertical spectral ratio (mHVSR) method thacan be valuable for identifying shallow rock sites. Finally, P- and SH-wave seismic refraction methods warrant consideration, especially at rock and shallow-rock sites.

Classification of Rigid Pavement at Airport Taxiway using Shear Wave Velocity and Elastic Modulus Derived from Spectral Analysis of Surface Waves (SASW) Method

Classification of Rigid Pavement at Airport Taxiway using Shear Wave Velocity and Elastic Modulus Derived from Spectral Analysis of Surface Waves (SASW) Method

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.

Prediction of Soil Settlement using Numerical Modelling Based on Shear Wave Velocity Measurement

The method of Spectral Analysis of Surface Wave (SASW) is a seismic method that consider as a non-destructive geotechnical technique to determine the soil profile based on the shear wave velocity profile by utilizing the dispersive characteristic of Rayleigh wave through the soil medium. The shear wave velocity was found to be directly proportional to the strength of the soil. In this research, SASW measurement had been proposed to predict the soil settlements using numerical modelling. The frequency responses from SASW were acquired for shear wave profile analysis using WinSASW software. Thus, the borehole information which near to the conventional pile method and SASW were taken as the reference of the study. In obtaining the correlated N-value, equation that developed from previous research was used with the reference of N-SPT value. Hence, the correlated N-values were carried forward to obtaining the bearing capacity of foundation. Meanwhile, the numerical modelling has been developed in PLAXIS software in obtaining the soil settlement. The prediction of soil settlements of Site 1, Site 2 and Site 3 that calculated by conventional equation and modelled using PLAXIS were 0.003mm and 0.001mm, 0.002mm and 0.004mm, 0.003mm and 0.004m respectively. Based on the result obtained, this research has shown the potential used of shear wave velocity in the prediction of soil settlement.

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.

Shear-wave velocity profiling of Jizan city, southwestern Saudi Arabia, using controlled-source spectral analysis of surface-wave measurements

Shear-wave velocity profiles are the main site-specific data for site classification, which are commonly used for the purposes of seismic microzonation and hazard assessment. The controlled-source spectral analysis of surface wave (CSSASW) dispersion measurements have been successfully performed to characterize seismic sites up to 30-m depths. This study utilizes the CSSASW application in Jizan City to obtain shear-wave velocity profiling at 14 sites distributed throughout the city using an electromagnetic vibrator. The recorded Rayleigh wave phase velocity dispersion curves are transformed to calculate the apparent velocity distribution in depth. Shear-wave velocities, calculated using theoretical relationships, can then be utilized to obtain design parameters for the soil strata. Shear-wave velocity varies from 216.97 to 829.59 m/s through Jizan City indicating the remarkable change of the near-surface sediments. The hard soil profiles of soft rock that were revealed by Vs values in this terrain (sites No. 7, 8, and 13) can be attributed to the existence of a dense layer of salt rock. Construction in such areas is prohibited due to the high susceptibility of large settlements in foundations as a consequence of salt dissolution. In the Sabkha terrains, all soil profiles were related to Vs, defined as stiff soils that were then modified to a softer class owing to their high liquefaction potential. These results should be considered before establishing important and strategic projects in the city.

Numerical modelling for prediction of ground-borne vibrations induced by pile driving

In this work, ground-borne vibrations due to pile driving impact are analyzed. A comparison between numerical results and experimental responses obtained in a low strain test measurement is presented. The experimental campaign is held at a construction site next to the Faculty of Engineering of the University of Porto (Portugal). The low strain test is carried out with 13 accelerometers equally distanced in a straight line and the ground vibrations are measured at the ground surface for several blows induced by an impact hammer. Soil properties and stratification are determined through non-intrusive geophysical tests - seismic refraction tests and SASW (Spectral Analysis of Surface Waves) tests. The numerical model is developed in time domain with the same characteristics of the construction site, considering a finite element axisymmetric formulation and an effective semi-explicit/explicit time marching procedure. The numerical results present good agreement with the in situ measured response, which indicates the effectiveness of the developed numerical model. In the sequence, a parametric study is developed and the results compared to previous numerical and experimental studies available in the literature.

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.

Liquefaction Susceptibility Assessment Using Geotechnical and Geological Manners of Northern Thailand

Soil site investigations such as boring logs, basic soil properties, spectral analysis of surface wave, and the examinations of geologic and geomorphologic were performed in Mae Lao area to investigate the susceptibility of liquefaction after the 6.2 Mw Chiang Rai Earthquake 2014. The study area was found to lay on a complex geological formation and geotechnical behavior with a condition of the high groundwater table. Being located on a high seismicity area (intensity V-VII Mercalli) governs the study area as a concern for high liquefaction hazards. Liquefaction susceptibility-based compositional criteria, soil resistance, and geologic criteria have been established, and consequently, the character of liquefaction potential is defined.

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.