A GIS-based multi-criteria evaluation framework for uncertainty reduction in earthquake disaster management using granular computing

One of the most important steps in earthquake disaster management is the prediction of probable damages which is called earthquake vulnerability assessment. Earthquake vulnerability assessment is a multicriteria problem and a number of multi-criteria decision making models have been proposed for the problem. Two main sources of uncertainty including uncertainty associated with experts‘ point of views and the one associated with attribute values exist in the earthquake vulnerability assessment problem. If the uncertainty in these two sources is not handled properly the resulted seismic vulnerability map will be unreliable. The main objective of this research is to propose a reliable model for earthquake vulnerability assessment which is able to manage the uncertainty associated with the experts‘ opinions. Granular Computing (GrC) is able to extract a set of if-then rules with minimum incompatibility from an information table. An integration of Dempster-Shafer Theory (DST) and GrC is applied in the current research to minimize the entropy in experts‘ opinions. The accuracy of the model based on the integration of the DST and GrC is 83%, while the accuracy of the single-expert model is 62% which indicates the importance of uncertainty management in seismic vulnerability assessment problem. Due to limited accessibility to current data, only six criteria are used in this model. However, the model is able to take into account both qualitative and quantitative criteria

Low transport stages by water streams of fine, cohesionless, granular and flakey sediments

Imperial Users onl

Informational Paradigm, management of uncertainty and theoretical formalisms in the clustering framework: A review

Fifty years have gone by since the publication of the first paper on clustering based on fuzzy sets theory. In 1965, L.A. Zadeh had published “Fuzzy Sets” [335]. After only one year, the first effects of this seminal paper began to emerge, with the pioneering paper on clustering by Bellman, Kalaba, Zadeh [33], in which they proposed a prototypal of clustering algorithm based on the fuzzy sets theory

Manufacturing of high precision mechanical components

The main goal of the thesis is to analyze key aspects of Precision Manufacturing, aiming at optimizing critical manufacturing processes: innovative experimental methodologies and advanced modelling techniques will be applied to cases study of industrial interest which have been successfully optimized

Elasto-plastic deformations within a material point framework on modern GPU architectures

Plastic strain localization is an important process on Earth. It strongly influ- ences the mechanical behaviour of natural processes, such as fault mechanics, earthquakes or orogeny. At a smaller scale, a landslide is a fantastic example of elasto-plastic deformations. Such behaviour spans from pre-failure mech- anisms to post-failure propagation of the unstable material. To fully resolve the landslide mechanics, the selected numerical methods should be able to efficiently address a wide range of deformation magnitudes. Accurate and performant numerical modelling requires important compu- tational resources. Mesh-free numerical methods such as the material point method (MPM) or the smoothed-particle hydrodynamics (SPH) are particu- larly computationally expensive, when compared with mesh-based methods, such as the finite element method (FEM) or the finite difference method (FDM). Still, mesh-free methods are particularly well-suited to numerical problems involving large elasto-plastic deformations. But, the computational efficiency of these methods should be first improved in order to tackle complex three-dimensional problems, i.e., landslides. As such, this research work attempts to alleviate the computational cost of the material point method by using the most recent graphics processing unit (GPU) architectures available. GPUs are many-core processors originally designed to refresh screen pixels (e.g., for computer games) independently. This allows GPUs to delivers a massive parallelism when compared to central processing units (CPUs). To do so, this research work first investigates code prototyping in a high- level language, e.g., MATLAB. This allows to implement vectorized algorithms and benchmark numerical results of two-dimensional analysis with analytical solutions and/or experimental results in an affordable amount of time. After- wards, low-level language such as CUDA C is used to efficiently implement a GPU-based solver, i.e., ep2-3De v1.0, can resolve three-dimensional prob- lems in a decent amount of time. This part takes advantages of the massive parallelism of modern GPU architectures. In addition, a first attempt of GPU parallel computing, i.e., multi-GPU codes, is performed to increase even more the performance and to address the on-chip memory limitation. Finally, this GPU-based solver is used to investigate three-dimensional granular collapses and is compared with experimental evidences obtained in the laboratory. This research work demonstrates that the material point method is well suited to resolve small to large elasto-plastic deformations. Moreover, the computational efficiency of the method can be dramatically increased using modern GPU architectures. These allow fast, performant and accurate three- dimensional modelling of landslides, provided that the on-chip memory limi- tation is alleviated with an appropriate parallel strategy

Behaviour of sandy soil subjected to dynamic loading

This thesis presents the kinematics occurring during lab-based dynamic compaction tests using high speed photography and image correlation techniques. High speed photography and X-ray microtomography have been used to analyse the behaviour of sandy soil subjected to dynamic impact. In particular, the densification mechanism of granular soils due to dynamic compaction is the main theme of the thesis. High speed photography and digital image correlation (DIC) techniques have enabled the deformation patterns, soil strains and strain localisations to be observed. Image correlation and X-ray scans revealed the formation, rate and growth of narrow tabular bands of intense deformation and significant volumetric change and provided answers towards a better understanding of the densification mechanism in dry granular soils due to dynamic compaction. As a quantitative tool, high speed photography has allowed the propagation of localised deformation and strain fields to be identified and has suggested that compaction shock bands control the kinematics of dynamic compaction. The displacement and strain results from high speed photography showed that soil deformation in the dynamic tests was dominated by a general bearing capacity mechanism similar to that widely stated in classic soil mechanics texts. Comparative static loading tests have been conducted to enable the dynamic effects to be clearly distinguished. This has enabled the densification process taking place below the soil surface to be investigated and identified. Simulations of the physical models were carried out using LS-DYNA finite element formulations for comparison and verification purposes. The FE simulations verified the general characteristics from the photography findings. However, simulation results were unable to predict the exact details of the strain localisation due to surface impacts during physical model tests

Behaviour of sandy soil subjected to dynamic loading

This thesis presents the kinematics occurring during lab-based dynamic compaction tests using high speed photography and image correlation techniques. High speed photography and X-ray microtomography have been used to analyse the behaviour of sandy soil subjected to dynamic impact. In particular, the densification mechanism of granular soils due to dynamic compaction is the main theme of the thesis. High speed photography and digital image correlation (DIC) techniques have enabled the deformation patterns, soil strains and strain localisations to be observed. Image correlation and X-ray scans revealed the formation, rate and growth of narrow tabular bands of intense deformation and significant volumetric change and provided answers towards a better understanding of the densification mechanism in dry granular soils due to dynamic compaction. As a quantitative tool, high speed photography has allowed the propagation of localised deformation and strain fields to be identified and has suggested that compaction shock bands control the kinematics of dynamic compaction. The displacement and strain results from high speed photography showed that soil deformation in the dynamic tests was dominated by a general bearing capacity mechanism similar to that widely stated in classic soil mechanics texts. Comparative static loading tests have been conducted to enable the dynamic effects to be clearly distinguished. This has enabled the densification process taking place below the soil surface to be investigated and identified. Simulations of the physical models were carried out using LS-DYNA finite element formulations for comparison and verification purposes. The FE simulations verified the general characteristics from the photography findings. However, simulation results were unable to predict the exact details of the strain localisation due to surface impacts during physical model tests

Development of a Computer Vision-Based Three-Dimensional Reconstruction Method for Volume-Change Measurement of Unsaturated Soils during Triaxial Testing

Problems associated with unsaturated soils are ubiquitous in the U.S., where expansive and collapsible soils are some of the most widely distributed and costly geologic hazards. Solving these widespread geohazards requires a fundamental understanding of the constitutive behavior of unsaturated soils. In the past six decades, the suction-controlled triaxial test has been established as a standard approach to characterizing constitutive behavior for unsaturated soils. However, this type of test requires costly test equipment and time-consuming testing processes. To overcome these limitations, a photogrammetry-based method has been developed recently to measure the global and localized volume-changes of unsaturated soils during triaxial test. However, this method relies on software to detect coded targets, which often requires tedious manual correction of incorrectly coded target detection information. To address the limitation of the photogrammetry-based method, this study developed a photogrammetric computer vision-based approach for automatic target recognition and 3D reconstruction for volume-changes measurement of unsaturated soils in triaxial tests. Deep learning method was used to improve the accuracy and efficiency of coded target recognition. A photogrammetric computer vision method and ray tracing technique were then developed and validated to reconstruct the three-dimensional models of soil specimen

Stabilization and Imaging of Cohesionless Soil Specimens

abstract: This dissertation describes development of a procedure for obtaining high quality, optical grade sand coupons from frozen sand specimens of Ottawa 20/30 sand for image processing and analysis to quantify soil structure along with a methodology for quantifying the microstructure from the images. A technique for thawing and stabilizing frozen core samples was developed using optical grade Buehler® Epo-Tek® epoxy resin, a modified triaxial cell, a vacuum/reservoir chamber, a desiccator, and a moisture gauge. The uniform epoxy resin impregnation required proper drying of the soil specimen, application of appropriate confining pressure and vacuum levels, and epoxy mixing, de-airing and curing. The resulting stabilized sand specimen was sectioned into 10 mm thick coupons that were planed, ground, and polished with progressively finer diamond abrasive grit levels using the modified Allied HTP Inc. polishing method so that the soil structure could be accurately quantified using images obtained with the use of an optical microscopy technique. Illumination via Bright Field Microscopy was used to capture the images for subsequent image processing and sand microstructure analysis. The quality of resulting images and the validity of the subsequent image morphology analysis hinged largely on employment of a polishing and grinding technique that resulted in a flat, scratch free, reflective coupon surface characterized by minimal microstructure relief and good contrast between the sand particles and the surrounding epoxy resin. Subsequent image processing involved conversion of the color images first to gray scale images and then to binary images with the use of contrast and image adjustments, removal of noise and image artifacts, image filtering, and image segmentation. Mathematical morphology algorithms were used on the resulting binary images to further enhance image quality. The binary images were then used to calculate soil structure parameters that included particle roundness and sphericity, particle orientation variability represented by rose diagrams, statistics on the local void ratio variability as a function of the sample size, and the local void ratio distribution histograms using Oda's method and Voronoi tessellation method, including the skewness, kurtosis, and entropy of a gamma cumulative probability distribution fit to the local void ratio distribution.Dissertation/ThesisM.S. Civil Engineering 201