Numerical and Data Analysis of a Portable Free Fall Penetremeter

Abstract

Coastal environments are among the most economically and environmentally significant regions on Earth. However, rising sea levels and increasingly frequent storms driven by climate change pose growing risks to these critical zones. Understanding and predicting the evolution of coastal environments requires advanced models and high-resolution geotechnical data to characterize the mechanical behavior of coastal soils. Portable free-fall penetrometers (PFFPs) are widely used for this purpose, offering a rapid and efficient means of collecting in situ soil data. Despite their utility, the interpretation of PFFP data remains uncertain due to the empirical nature of existing methods used to infer soil properties from impact acceleration measurements. This research aims to improve the reliability of PFFP-based soil characterization by advancing both numerical modeling and data processing techniques. To this end, a two-pronged approach was taken. First, efforts were made to refine and streamline numerical modeling techniques to work towards the creation of a digital twin of BlueDrop PFFP impacting into the soil. This included identifying the current limitations of the MPM framework to simulate PFFP impact and addressing some of these limitations. In particular, this thesis focuses on the mitigation of volumetric locking by means of the implementation of the B-Bar algorithm in quadrilateral elements and the availability of strain-rate advanced consecutive models by testing the accuracy and efficiency of different stress integration algorithms. In addition, a Python library was also developed to streamline the testing of soil constitutive models using the IncrementalDriver software. Second, the processing of BlueDrop field data was centralized, standardized, and automated through the development of a Python library integrated with an SQLite database. This ensures consistency and accessibility of PFFP datasets for broader scientific and engineering applications. By advancing data processing methodologies and improving numerical modeling capabilities, this research contributes to a more rigorous framework for interpreting PFFP measurements and understanding soil behavior during impact. These developments support broader efforts to enhance geotechnical modeling of coastal systems, ultimately aiding in the prediction and management of environmental changes affecting these vulnerable regions.