Laboratory Small-Strain Stiffness Measurement Using Distributed Acoustic Sensing

This article introduces a novel method for measuring the small-strain stiffness of materials at the laboratory scale using the emerging technology of distributed acoustic sensing (DAS). This setup involves modifying the traditional free-free resonant column test by wrapping the DAS fiber optic cable around the sample. Tests are conducted using both active and passive sources. Sample resonances measured by DAS demonstrate a high degree of consistency with conventional accelerometer, indicating that DAS is accurate and reliable at the kilohertz scale. To extract the sample resonant frequency from passive sources in laboratory environments (such as cooling fan noise, mixer vibrations, and manual tamping procedure), the auto correlation method is employed to enhance the amplitude spectrum's signal-to-noise ratio. The measured transverse resonance excited by passive sources aligns well with that measured under active sources, suggesting the potential for using nonstationary ambient vibrations for long-term monitoring. The study also reveals that impulse-like forces are more suitable for exciting distinguishable resonant frequency compared to continuous but weak ambient vibrations. In a benchmark study, the repeatability of DAS measurements is verified using fabricated samples with known and stable stiffness. The measured constrained and shear moduli are found to be consistent among DAS, accelerometer, and ground-truth values, confirming the robustness and accuracy of the DAS-based free-free resonance column test. To further demonstrate the practical application of the proposed DAS-based system, a 28-day monitoring of cement-stabilized soil is conducted. The small-strain stiffness evolution is successfully captured by DAS, with marginal differences between measurements under active and passive sources. This outcome highlights the potential quality assurance scenarios for DAS because of its distributed properties and rapid data acquisition capabilities.