Soft fine-grained sediments placed by hydraulic dredging usually pass through two main stages: an initial sedimentation stage, where particles settle in suspension, and a later self-weight consolidation stage, where interparticle contacts develop and pore water is progressively expelled. In engineering practice, these two stages are often treated separately, which makes it difficult to describe the full evolution of very soft deposits within a single consistent model. This paper presents a unified finite element framework for sedimentation and consolidation of diluted clay suspensions. The formulation is based on a common set of governing equations and constitutive relations, allowing both regimes to be described within one continuous advection–diffusion framework. A smooth transition around the gelling concentration is introduced to avoid a discontinuous switch between sedimentation and consolidation, and a SUPG stabilization is used for advection-dominated transport. The model is applied to kaolinite K1 and Marker Wadden mud, and the results are compared with experimental measurements of interface evolution, density profiles, and drainage-induced settlement. The framework reproduces the main trends observed in both one-dimensional settling columns and drainage-controlled configurations. In addition, the formulation is compared with a large-strain finite element reference model using logarithmic compressibility, showing that the proposed approach remains consistent with more advanced hydro-mechanical descriptions while retaining a simpler constitutive structure that avoids tensorial stress updates, return-mapping algorithms, and additional internal variables. The proposed framework provides a practical tool for analyzing the evolution of very soft sediments from suspension to consolidated soil in geotechnical and land reclamation applications.

This study presents a method to determine surface relaxivity in soft sediments by combining one-dimensional Nuclear Magnetic Resonance (NMR) imaging with particle size and shape estimates. In order to determine the surface relaxivity up to now often methods like Mercury Intrusion Porosimetry or Brunauer–Emmett–Teller (BET) are used which where drying steps are involved which can alter material properties during analysis, particularly in highly deformable materials, making these techniques unreliable for soft soils. By combining NMR relaxometry and estimates of particle sizes and shapes of a soft soil, this new approach provides accurate, non-invasive surface relaxivity measurements. This method is demonstrated on kaolinite, glass beads, and natural soils, showing that this method supports detailed assessment of pore size distributions in soft sediments, benefiting geotechnical and environmental research where soil stability is critical.

This paper proposes a new technique for the 3D identification of clay particle orientations using images obtained from FIB-SEM observations. The method is based on a three-dimensional reconstruction that combines the Focused Ion Beam abrasion technique and Scanning Electron Microscopy, applied to kaolinitic clay selected for this study. The clay was first subjected to one-dimensional compression up to a given stress level, after which microstructural observations were performed using a post-mortem approach. A novel methodology using appropriate image processing was established for this purpose, allowing for a precise treatment of the obtained FIB-SEM images. The proposed methodology first involved removing “curtain effects” and “charging artefact”, which are specific types of noise commonly associated with FIB-SEM images. Two methods were employed to address this issue and were compared to evaluate their effectiveness: the first method was based on Fourier Transformation and Total Variational Reconstruction, while the second used a stochastic approach formulated as a convex optimization problem. Subsequently, a machine learning technique was integrated to enhance the segmentation process of the images. The final stage of the methodology involved creating a 3D model by reconstructing the clay particles in their spatial configuration. This paper aims to demonstrate how the proposed 3D observation method enables the quantification of the structural organization of clay particles in space in relation to mechanical loading.