Effect of soil properties on the response of pile to underground explosion

This paper develops and presents a fully coupled non-linear finite element procedure to treat the response of piles to ground shocks induced by underground explosions. The Arbitrary Lagrange Euler coupling formulation with proper state material parameters and equations are used in the study. Pile responses in four different soil types, viz, saturated soil, partially saturated soil and loose and dense dry soils are investigated and the results compared. Numerical results are validated by comparing with those from a standard design manual. Blast wave propagation in soils, horizontal pile deformations and damages in the pile are presented. The pile damage presented through plastic strain diagrams will enable the vulnerability assessment of the piles under the blast scenarios considered. The numerical results indicate that the blast performance of the piles embedded in saturated soil and loose dry soil are more severe than those in piles embedded in partially saturated soil and dense dry soil. Present findings should serve as a benchmark reference for future analysis and design.

A novel approach for numerical simulation of plant tissue shrinkage during drying

Drying is a key processing techniques used in food engineering which demands continual developments on advanced analysis techniques in order to optimize the product and the process. In this regard, plant based materials are a frequent subject of interest where microstructural studies can provide a clearer understanding on the fundamental physical mechanisms involved. In this context, considering numerous challenges of using conventional numerical grid-based modelling techniques, a meshfree particle based model was developed to simulate extreme deformations of plant microstructure during drying. The proposed technique is based on a particle based meshfree method: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). A tissue model was developed by aggrading individual cells modelled with SPH-DEM coupled approach by initializing the cells as hexagons and aggregating them to form a tissue. The model also involves a middle lamella resembling real tissues. Using the model, different dried tissue states were simulated with different moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model is capable of simulating plant tissues at lower moisture contents which results in excessive shrinkage and cell wall wrinkling. Model predictions were compared with experimental findings and a fairly good agreement was observed both qualitatively and quantitatively.

A meshfree particle based model for microscale shrinkage mechanisms of food materials in drying conditions

Cells are the fundamental building block of plant based food materials and many of the food processing born structural changes can fundamentally be derived as a function of the deformations of the cellular structure. In food dehydration the bulk level changes in porosity, density and shrinkage can be better explained using cellular level deformations initiated by the moisture removal from the cellular fluid. A novel approach is used in this research to model the cell fluid with Smoothed Particle Hydrodynamics (SPH) and cell walls with Discrete Element Methods (DEM), that are fundamentally known to be robust in treating complex fluid and solid mechanics. High Performance Computing (HPC) is used for the computations due to its computing advantages. Comparing with the deficiencies of the state of the art drying models, the current model is found to be robust in replicating drying mechanics of plant based food materials in microscale.

Soil-pile interaction of pile embedded in deep layered marine sediment under seismic excitation

This research provides validated Finite Element techniques to analyse pile foundations under seismic loads. The results show that the capability of the technique to capture the important pile response which includes kinematic and inertial interaction effects, effects of soil stiffness and depth on pile deflection patterns and permanent deformations.

Numerical simulation of micro-scale morphological changes of plant food materials during drying - a meshfree approach

This thesis developed a high preforming alternative numerical technique to investigate microscale morphological changes of plant food materials during drying. The technique is based on a novel meshfree method, and is more capable of modeling large deformations of multiphase problem domains, when compared with conventional grid-based numerical modeling techniques. The developed cellular model can effectively replicate dried tissue morphological changes such as shrinkage and cell wall wrinkling, as influenced by moisture reduction and turgor loss.

Deformation of a three-dimensional red blood cell in a stenosed micro-capillary

Red blood cells (RBCs) exhibit different types of motions and deformations when the blood flows through capillaries. Interestingly, due to the complex three-dimensional structure of the RBC membrane, RBCs show three-dimensional motions and deformations in the blood flow. These motions and deformations of the RBCs highly depend on the stiffness of the RBC membrane and on the geometrical parameters of the capillary through which blood flows. However, capillaries always do not have uniform cross sections and some capillaries have stenosed segments, where cross sectional area suddenly reduces. Further, some diseases can alter the stiffness of the RBC membrane drastically. In this study, the deformation behaviour of a single three-dimensional RBC is examined, when it moves through a stenosed capillary. A three-dimensional spring network is used to model the RBC membrane. The RBC’s inside and outside fluids are discretized into a finite number of mass points and treated by smoothed particle hydrodynamics (SPH) method. The capillary is considered as a rigid tube with a stenosed section. The deformation index, mean velocity and total energy of the RBC are analysed when it flows through the stenosed capillary. Further, motion and deformation of the RBCs with different membrane stiffness (KB) are compared when they flow through the stenosed segment of the capillary. The simulation results demonstrate the RBCs are subjected to a larger deformation when they move through the stenosed part of the capillary and the RBCs with lower KBvalues easily pass through the stenosed segment of the capillary. Further, RBCs having higher KBvalues have a lower mean velocity and it leads to slow down the overall blood flow rate

Numerical investigation of plant tissue porosity and its influence on cellular level shrinkage during drying

Dried plant food products are increasing in demand in the consumer market, leading to continuing research to develop better products and processing techniques. Plant materials are porous structures, which undergo large deformations during drying. For any given food material, porosity and other cellular parameters have a direct influence on the level of shrinkage and deformation characteristics during drying, which involve complex mechanisms. In order to better understand such mechanisms and their interrelationships, numerical modelling can be used as a tool. In contrast to conventional grid-based modelling techniques, it is considered that meshfree methods may have a higher potential for modelling large deformations of multiphase problem domains. This work uses a meshfree based microscale plant tissue drying model, which was recently developed by the authors. Here, the effects of porosity have been newly accounted for in the model with the objective of studying porosity development during drying and its influence on shrinkage at the cellular level. For simplicity, only open pores are modelled and in order to investigate the influence of different cellular parameters, both apple and grape tissues were used in the study. The simulation results indicated that the porosity negatively influences shrinkage during drying and the porosity decreases as the moisture content reduces (when open pores are considered). Also, there is a clear difference in the deformations of cells, tissues and pores, which is mainly influenced by the cell wall contraction effects during drying.

Numerical investigation of case hardening of plant tissue during dying and its influence on the cellular level shrinkage

Dried plant food materials are one of the major contributors to the global food industry. Widening the fundamental understanding on different mechanisms of food material alterations during drying assists the development of novel dried food products and processing techniques. In this regard, case hardening is an important phenomenon, commonly observed during the drying processes of plant food materials, which significantly influences the product quality and process performance. In this work, a recent meshfree-based numerical model of the authors is further improved and used to simulate the influence of case hardening on shrinkage characteristics of plant tissues during drying. In order to model fluid and wall mechanisms in each cell, Smoothed Particle Hydrodynamics (SPH) and the Discrete Element Method (DEM) are used. The model is fundamentally more capable of simulating large deformation of multiphase materials, when compared with conventional grid-based modelling techniques such as Finite Element Methods (FEM) or Finite Difference Methods (FDM). Case hardening is implemented by maintaining distinct moisture levels in the different cell layers of a given tissue. In order to compare and investigate different factors influencing tissue deformations under case hardening, four different plant tissue varieties (apple, potato, carrot and grape) are studied. The simulation results indicate that the inner cells of any given tissue undergo limited shrinkage and cell wall wrinkling compared to the case hardened outer cell layers of the tissues. When comparing unique deformation characteristics of the different tissues, irrespective of the normalised moisture content, the cell size, cell fluid turgor pressure and cell wall characteristics influence the tissue response to case hardening.

Fluid registration of diffusion tensor images using information theory

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or $J$-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the $J$-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

4D deformation modeling of cortical disease progression in Alzheimer's dementia

This work describes the development of a model of cerebral atrophic changes associated with the progression of Alzheimer's disease (AD). Linear registration, region-of-interest analysis, and voxel-based morphometry methods have all been employed to elucidate the changes observed at discrete intervals during a disease process. In addition to describing the nature of the changes, modeling disease-related changes via deformations can also provide information on temporal characteristics. In order to continuously model changes associated with AD, deformation maps from 21 patients were averaged across a novel z-score disease progression dimension based on Mini Mental State Examination (MMSE) scores. The resulting deformation maps are presented via three metrics: local volume loss (atrophy), volume (CSF) increase, and translation (interpreted as representing collapse of cortical structures). Inspection of the maps revealed significant perturbations in the deformation fields corresponding to the entorhinal cortex (EC) and hippocampus, orbitofrontal and parietal cortex, and regions surrounding the sulci and ventricular spaces, with earlier changes predominantly lateralized to the left hemisphere. These changes are consistent with results from post-mortem studies of AD.

A new combined surface and volume registration

3D registration of brain MRI data is vital for many medical imaging applications. However, purely intensitybased approaches for inter-subject matching of brain structure are generally inaccurate in cortical regions, due to the highly complex network of sulci and gyri, which vary widely across subjects. Here we combine a surfacebased cortical registration with a 3D fluid one for the first time, enabling precise matching of cortical folds, but allowing large deformations in the enclosed brain volume, which guarantee diffeomorphisms. This greatly improves the matching of anatomy in cortical areas. The cortices are segmented and registered with the software Freesurfer. The deformation field is initially extended to the full 3D brain volume using a 3D harmonic mapping that preserves the matching between cortical surfaces. Finally, these deformation fields are used to initialize a 3D Riemannian fluid registration algorithm, that improves the alignment of subcortical brain regions. We validate this method on an MRI dataset from 92 healthy adult twins. Results are compared to those based on volumetric registration without surface constraints; the resulting mean templates resolve consistent anatomical features both subcortically and at the cortex, suggesting that the approach is well-suited for cross-subject integration of functional and anatomic data.

Formation of highly conductive composite coatings and their applications to broadband antennas and mechanical transducers

Tight networks of interwoven carbon nanotube bundles are formed in our highly conductive composite. The composite possesses propertiessuggesting a two-dimensional percolative network rather than other reported dispersions displaying three-dimensional networks. Binding nanotubes into large but tight bundles dramatically alters the morphology and electronic transport dynamics of the composite. This enables itto carry higher levels of charge in the macroscale leading to conductivities as high as 1600 S/cm. We now discuss in further detail, the electronic and physical properties of the nanotube composites through Raman spectroscopy and transmission electron microscopy analysis. When controlled and usedappropriately, the interesting properties of these composites reveal their potential for practical device applications. For instance, we used this composite to fabricate coatings, whic improve the properties of an electromagnetic antenna/amplifier transducer. The resulting transducer possesses a broadband range up to GHz frequencies. A strain gauge transducer was also fabricated using changes in conductivity to monitor structural deformations in the composite coatings.

On robust face recognition via sparse coding: The good, the bad and the ugly

In the field of face recognition, sparse representation (SR) has received considerable attention during the past few years, with a focus on holistic descriptors in closed-set identification applications. The underlying assumption in such SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such an assumption is easily violated in the face verification scenario, where the task is to determine if two faces (where one or both have not been seen before) belong to the same person. In this study, the authors propose an alternative approach to SR-based face verification, where SR encoding is performed on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which then form an overall face descriptor. Owing to the deliberate loss of spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment and various image deformations. Within the proposed framework, they evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN) and an implicit probabilistic technique based on Gaussian mixture models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, on both the traditional closed-set identification task and the more applicable face verification task. The experiments also show that l1-minimisation-based encoding has a considerably higher computational cost when compared with SANN-based and probabilistic encoding, but leads to higher recognition rates.

Damage assessment of basaltic rock mass due to repeated blasting in a railway tunnelling project - A case study

The demand for tunnelling and underground space creation is rapidly growing due to the requirement of civil infrastructure projects and urbanisation. Blasting remains the most inexpensive method of underground excavations in hard rock. Unfortunately, there are no specific safety guidelines available for the blasted tunnels with regards to the threshold limits of vibrations caused by repeated blasting activity in the close proximity. This paper presents the results of a comprehensive study conducted to find out the effect of repeated blast loading on the damage experienced by jointed basaltic rock mass during tunnelling works. Conducting of multiple rounds of blasts for various civil excavations in a railway tunnel imparted repeated loading on rock mass of sidewall and roof of the tunnel. The blast induced damage was assessed by using vibration attenuation equations of charge weight scaling law and measured by borehole extensometers and borehole camera. Ground vibrations of each blasting round were also monitored by triaxial geophones installed near the borehole extensometers. The peak particle velocity (V-max) observations and plastic deformations from borehole extensometers were used to develop a site specific damage model. The study reveals that repeated dynamic loading imparted on the exposed tunnel from subsequent blasts, in the vicinity, resulted in rock mass damage at lesser vibration levels than the critical peak particle velocity (V-cr). It was found that, the repeated blast loading resulted in the near-field damage due to high frequency waves and far-field damage due to low frequency waves. The far field damage, after 45-50 occurrences of blast loading, was up to 55% of the near-field damage in basaltic rock mass. The findings of the study clearly indicate that the phenomena of repeated blasting with respect to number of cycles of loading should be taken into consideration for proper assessment of blast induced damage in underground excavations.