Efficient modelling of 3-d finite element mesh formation with use of 3-d topographic survey

In this decade, 3-dimensional topographic survey has been developed by using the UAV as like drones. With the technique, the complete topographies of the geo-structures can be measured. Although the accurate shapes of the geo-structures can be obtained, the numerical methods as like the finite element method is are not related to the 3-dimensional survey directly. In this research, the finite mesh modelling technique with use of the 3-D topographic survey is developed. The models of the earth-fill embankments formed from measured 3-D data are introduced as the examples

An iterative Bayesian filtering framework for fast and automated calibration of DEM models

The nonlinear, history-dependent macroscopic behavior of a granular material is rooted in the micromechanics between constituent particles and irreversible, plastic deformations reflected by changes in the microstructure. The discrete element method (DEM) can predict the evolution of the microstructure resulting from interparticle interactions. However, micromechanical parameters at contact and particle levels are generally unknown because of the diversity of granular materials with respect to their surfaces, shapes, disorder and anisotropy. The proposed iterative Bayesian filter consists in recursively updating the posterior distribution of model parameters and iterating the process with new samples drawn from a proposal density in highly probable parameter spaces. Over iterations the proposal density is progressively localized near the posterior modes, which allows automated zooming towards optimal solutions. The Dirichlet process Gaussian mixture is trained with sparse and high dimensional data from the previous iteration to update the proposal density. As an example, the probability distribution of the micromechanical parameters is estimated, conditioning on the experimentally measured stress–strain behavior of a granular assembly. Four micromechanical parameters, i.e., contact-level Young’s modulus, interparticle friction, rolling stiffness and rolling friction, are chosen as strongly relevant for the macroscopic behavior. The a priori particle configuration is obtained from 3D X-ray computed tomography images. The a posteriori expectation of each micromechanical parameter converges within four iterations, leading to an excellent agreement between the experimental data and the numerical predictions. As new result, the proposed framework provides a deeper understanding of the correlations among micromechanical parameters and between the micro- and macro-parameters/quantities of interest, including their uncertainties. Therefore, the iterative Bayesian filtering framework has a great potential for quantifying parameter uncertainties and their propagation across various scales in granular materials

Identification of Spatial Distribution of Permeability in Dikes by CPTs

In this study, the spatial variability of the strength and permeability inside and underneath a river dike are addressed. Cone penetration tests (CPTs) were conducted at the river dike site, which has piping histries. In addition, CPTs were conducted in the laboratory as model tests on soil sampled from the river dike site, and permeability tests were also conducted on the same samples. Based on the laboratory tests, the relationship between the CPT results, which include the tip resistance, the side friction, and the pore pressure, and the permeability is derived. The relationship is applied to the in-situ test results. In conclusion, the spatial variability of the strength and permeability of the test site is evaluated with a geostatistical simulation technique

Reliability-based design for earth-fill dams against severe natural disaster events

The maintenance of geotechnical structures, such as earth-fill dams, is required as a countermeasure against severe natural disasters, particularly earthquakes and heavy rains. The reliability-based analysis introduced here is in response to the recent demand for low-cost improvements.First, a statistical model of N values was determined from Swedish weight sounding (SWS) tests to present the spatial variability of the soil strength. Then, a reliability-based analysis of embankments was conducted by considering the variability of the internal friction angle derived from N value, and the seismic hazard for the Nankai Trough. The next step was to evaluate the probability of the overflow of earth-fills during heavy rains. The rainfall intensity was considered as a probabilistic parameter, and the various rainfall patterns were tested by the proposed method. Finally, the total risk due to both earthquakes and heavy rains was evaluated for an earth-fill site. As a result, the possibility for the practical use of the proposed method in making plans for the maintenance of deteriorated earth-fill dams was verified