Particle breakage is of fundamental importance for understanding the mechanical behaviour of sands and is relevant to many geotechnical engineering problems. In order to gain new insights into the mechanism of breakage of individual sand particles under single-particle compression, this study combines mechanical tests with three-dimensional X-ray micro-computed tomography (μCT) performed 'in situ', that is, during loading. A novel mini-loading apparatus was developed to perform in-situ compression tests within a laboratory nanofocus X-ray CT. The tests were performed on eight particles, four Leighton Buzzard sand (LBS) particles and four highly decomposed granite (HDG) particles, to study their different fracture mechanisms. A series of image processing and analysing techniques was utilised to obtain both qualitative and quantitative results. The most important factors in determining the fracture patterns of the LBS and HDG particles were found to be particle morphology and initial microstructure, respectively. Versatile fracture patterns deviating from simple vertical splitting were observed, particularly in HDG particles. The change of morphology parameters during loading was found to depend on the fracture mechanisms and material properties, independently of their initial values. The fragments of both the LBS and HDG particles satisfy the fractal distribution, which indicates that the fragmentation is scale invariant. Different energy dissipation mechanisms were found. The energy dissipation by friction gradually prevails against the energy dissipated in generating new surfaces.

Particle shape plays an important role in determining the engineering behaviour of granular materials. In this regard, characterisation and quantification of particle shape are essential for understanding the behaviour of granular materials. X-ray micro-computed tomography (μCT) enables observation of particle morphology at ever-greater resolutions. The challenge has thus become extracting quantified shape parameters from these rich three-dimensional (3D) images. In this paper, we implement X-ray μCT to obtain 3D particle morphology and utilize image processing and analysis techniques to quantify it at different scales. A novel framework is proposed to measure 3D shape parameters of form, roundness, and compactness. New 3D roundness indexes were formulated from the local curvature on reconstructed triangular surface mesh. Subsequently, this method is utilized to study the change of particle shape by single particle crushing tests on Leighton Buzzard sand (LBS) particles. It is found that compactness value (i.e., sphericity) could be influenced by both form and roundness. Then, the distributions of shape parameters are characterised by Weibull statistics. It shows that single particle crushing tests generate more irregular fragments which have smaller shape parameters with larger variance for the measured shape parameters.

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The migration and retention of fine particles in porous media are important phenomena in natural processes and engineering applications. Migrating particles experience physicochemical interactions with carrier fluids, pore walls, and other migrating particles. The governing dimensionless ratios capture particle‐level forces, flow conditions, and geometric characteristics. This study explores micron‐size particle migration and retention in microfluidic chips during convergent radial flow, which is the prevalent flow condition in water extraction and oil production. Pore‐scale observations reveal the role of electrostatic interactions on clogging mechanisms: Glass particles experience retardation‐accumulation bridging, while quasi‐buoyant latex particles involve capture and clogging. Consequently, flow rates exert opposite effects on the clogging behavior of inertial glass particles versus electrostatically affected latex particles. Migrating particles experience a varying fluid velocity field in convergent radial flow, and clogging reflects the evolving local conditions (Nad, Ar, Stk, and Re). In particular, clogged pores alter local flow and promote further clogging nearby. Pore network model simulations suggest that such “dependent clogging” lowers the permeability of the porous medium more effectively than independent clogging at random locations.

SUMMARYThis paper presents the applications of the differential evolution (DE) algorithm in back analysis of soil parameters for deep excavation problems. A computer code, named Python-based DE, is developed and incorporated into the commercial finite element software ABAQUS, with a parallel computing technique to run an FE analysis for all trail vectors of one generation in DE in multiple cores of a cluster, which dramatically reduces the computational time. A synthetic case and a well-instrumented real case, that is, the Taipei National Enterprise Center (TNEC) project, are used to demonstrate the capability of the proposed back-analysis procedure. Results show that multiple soil parameters are well identified by back analysis using a DE optimization algorithm for highly nonlinear problems. For the synthetic excavation case, the back-analyzed parameters are basically identical to the input parameters that are used to generate synthetic response of wall deflection. For the TNEC case with a total of nine parameters to be back analyzed, the relative errors of wall deflection for the last three stages are 2.2, 1.1, and 1.0%, respectively. Robustness of the back-estimated parameters is further illustrated by a forward prediction. The wall deflection in the subsequent stages can be satisfactorily predicted using the back-analyzed soil parameters at early stages.