Abstract Gap-graded cohesionless soils are extensively utilized in numerous man-made geotechnical structures such as earthen embankments, man-made fills and used for the prevention of seepage in dams and tailings of… Click to show full abstract
Abstract Gap-graded cohesionless soils are extensively utilized in numerous man-made geotechnical structures such as earthen embankments, man-made fills and used for the prevention of seepage in dams and tailings of mines. However, there is a lack of research available on investigating the transitional behaviour of frequency responses of gap-graded cohesionless soils. Therefore, the present research explores the stress wave transmission in gap-graded silica sand mixtures (having median particle size ratio of 6.4) using disk-shaped piezoelectric transducers (DTs). By employing DTs, shear (Vs) and compression (Vp) wave velocities are measured using more planar waves and eliminate the possibility of fine particle segregation commonly encountered during insertion of bender elements. The experimental results indicate that at an equivalent void ratio, Vs and Vp decrease initially with the increase in fine silica sand content (Fs); however, once a transitional value (Fs,thr) is attained, Vs and Vp start to rise and move towards the values for fine silica sand. Such transitional behaviours of elastic wave velocities and frequency-domain responses are dependent on the state of packing, i.e. denser specimens achieve this at a lower Fs than the looser equivalents. It is observed that for a given Fs, there exists a linear relationship between the maximum transmitted frequency in the packing, i.e. low-pass frequency (flp) and the Vs. Furthermore, a novel approach has been described by which the type of gap-graded mixture, i.e. underfilled (internally unstable) or overfilled (stable), can be assessed by experimentalists from the slope of flpāVsresponses. The advantage of adopting flp to categorize the gap-graded mixtures is that the same is more sensitive to Fs in comparison to Vs or Vp, and thus a more robust analysis can be achieved.
               
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