Smart offshore site investigation using free fall penetrometers

PhD student

Parviz Tafazzoli Moghaddam

Supervisors

Dr Negin Yousefpour	A/Prof Shiaohuey Chow	Prof Mark Cassidy

Project Start Date: Decembery 2023

Project Details

Penetrometers are commonly used to estimate the mechanical properties of soils. However, for sites that are relatively inaccessible, such as many seabed soil deposits, some in-situ tests such as the static cone penetration test are not functional. Therefore, the Free Fall Penetrometer (FFP) is a more practical alternative for the characterization of nearshore and offshore sediments because it is a time-efficient, cost-effective, and versatile test and it can be deployed from small vessels. On the one hand, performing in-situ tests at small spatial intervals is impractical in many cases. On the other hand, the soil stratum is heterogeneous and its properties have noticeable uncertainty and variability making predicting the soil parameters of the unsampled regions challenging. Moreover, Interpreting the soil properties from the FFP data involves a high amount of uncertainty. Thus, the costs and time needed for a suitable site investigation program can be reduced significantly by Probabilistic analysis such as the Bayesian method and Machine Learning algorithms. These algorithms are capable of spatial prediction of soil properties and their degree of inherent variability.