The UTexas 1 surface wave dataset was collected at a site in Christchurch, New Zealand. The dataset contains active-source, linear-array data and ambient wavefield, circular-array data. Only the active-source data were analyzed using the spectral-analysis-of-surface-waves (SASW) methodology. The dispersion and forward modeling procedures are documented in the paper. Forward modeling was performed using both the 3-D global and 3-D array-based procedures. A well-constrained V_s profile was determined to a depth of about 140 m. In forward modeling, effective-mode transitions were identified in the dataset. As such, the correct V_s profile could not be determined if it were assumed that the field data represented only the fundamental mode.

Dynamic deflection of a railroad sleeper works as an indicator of ballast stiffness, reflecting the health conditions of a ballast track. However, difficulty exists in measuring dynamic deflection of a railroad sleeper by conventional deflection transducers such as a linear variable differential transformer (LVDT) or a potentiometer. This is because a fixed reference point is unattainable due to ground vibrations during train passage. In this paper, a patented signal processing technique for evaluation of pseudo-deflection is presented to recover dynamic deflection of a railroad sleeper using a coupled measurement of acceleration and strain at the concrete sleeper. The presented technique combines high-frequency deflections calculated from double integration of acceleration and low-frequency deflections determined from strains. Validity of the combined deflections was shown by the deflections measured with a camera target on a concrete sleeper, captured by a high-resolution DSLR camera with superb video capturing features and processed by computer vision techniques, such as Canny edge detection and Blob analysis.

Compressive strength of concrete is a very important parameter in the quality control of both new and existing concrete pavement. It has been widely used to evaluate the concrete strength both in the laboratory and in the construction field regardless of whether numerous mix designs or identical mixtures are used. Errors usually happen in the compressive strength test even if the mixture is evenly mixed and compacted into test specimens. This is caused by either by the hand-operated testing machine or by the eccentricity between the specimen and the testing machine. If concrete specimens with identical mix design need to be tested at various curing ages every time concrete is used in the construction field, the result is significant waste of time, money and efforts are required. Consequently, there is a real need to replace the repeated compressive strength tests with the introduction of nondestructive tests to estimate compressive strength of concrete. In this study, a nondestructive test method using elastic waves was used because shear wave velocity is not affected by restraint conditions. The compressive strength of concrete was estimated according to various curing ages as well. In the results, shear wave velocity was very closely related to the compressive strength. The results further showed that the estimation of compressive strength of concrete using shear wave velocity is very effective and reliable.

The discrepancy among results of various surface-wave tests is reported. In Korea, universities and industries collaborated to compare the reliability of surface waves including the Spectral-Analysis-of-Surface-Waves (SASW) method, the Multichannel Analysis of Surface Waves (MASW) method, the Harmonic Wavelet Analysis of Waves method (HWAW) and the Refraction Microtremor (ReMi) method at a given geological site. The resulting shear-wave velocity profiles were compared with borehole seismic test results. Also, the stratification evaluated by surface-wave tests is compared with the stratification by borehole logs and SPT-N values. The distinct difference between the SASW and the MASW methods was identified in the depth resolution of the 1-D shear wave velocity and in the accuracy of the 2-D spatial profiling of subsurface stiffness. The effects of seismic source, the sensitivity of sensors and the forward modeling theory are discussed to explain the discrepancy between the SASW method and the MASW method.

Many surface-wave methods have focused on collecting only normal modes of Rayleigh-wave propagation. This paper presents an inversion algorithm to invert the apparent phase velocities, which include near-field information as well as normal-mode information. In the algorithm, Love-wave dispersion data are jointly included with Rayleigh-wave dispersion data to reduce non-uniqueness inherent in surface-wave methods and increase the accuracy of a resulting shear-wave velocity profile. Synthetic dispersion data were generated for typical geologic sites, and used for the verification of the inversion algorithm. A strategy to overcome the adverse effects of multiple reflections and mode conversion in Love waves is also discussed.

This paper presents the feasibility of using Scholte waves by spectral-analysis-of-surface-waves (SASW) method for near-surface soil stiffness profiling. Scholte-wave measurement does not require ground coupling thus fast SASW can be performed. Scholte wave propagation at the air-to-soil interface was analyzed first by Finite Element (FE) simulation. In the FE model, a coupled acoustic-structural model was employed to simulate Scholte-wave propagation and acoustic wave contamination were controlled by sensor insulation. Field testing at several compaction sites based on FE results was performed. We found that the dispersion curve of Scholte waves agrees well with Rayleigh-wave dispersion curve if sensors are perfectly insulated. Higher phase velocity is observed when Scholte waves are interrupted by acoustic wave. However, 1 cm opening at the bottom of insulated microphone can be considered as perfect insulation.