Numerical modelling of hydrodynamic pressures on dams

This paper discusses several considerations related to appropriate numerical modelling of the reservoir hydrodynamic pressures on dams. The reservoir is modelled with 8-noded isoparametric displacement based solid finite elements. The study includes both stiff and flexible dams with vertical and sloped upstream faces under ramp, harmonic and random acceleration loads. The numerical results were compared and found to be in good agreement with available closed-form solutions. The same approach may be used in analyses of other waterfront structures such as quay walls. © 2013 Elsevier Ltd.

Hydrodynamic pressures behind flexible and rigid dams

During earthquakes, hydrodynamic pressures are generated by the impounded reservoir on the dam face. The magnitude and distribution of the hydrodynamic pressures vary with factors such as frequency and intensity of earthquake-induced ground motion, depth of impounded reservoir, stiffness of dam and geological conditions. It is difficult to obtain experimental data on hydrodynamic pressures from the field owing to uncertainties associated with earthquake loading. This paper aims at using dynamic centrifuge modelling to measure hydrodynamic pressures behind both relatively stiff and flexible model dams. Comparisons of the experimental data with theoretical hydrodynamic pressures show that Westergaard's equation gives a conservative estimation of hydrodynamic pressures. Comparison with Chopra's method revealed that it underpredicts hydrodynamic pressures for low reservoir depths but gives reasonably good predictions for higher depths of reservoir. It is concluded that dynamic centrifuge modelling may be an effective experimental method to estimate the hydrodynamic pressures acting on a dam. © 2010 Thomas Telford Ltd.

Characteristics of blood flow in microchannels and relevant impact on modelling blood behaviour in biochip separators

This paper reports a perspective investigation of computational modelling of blood fluid in microchannel devices as a preparation for future research on fluid-structure interaction (FSI) in biofluid mechanics. The investigation is carried out through two aspects, respectively on physical behaviours of blood flow in microchannels and appropriate methodology for modelling. The physics of blood flow is targeted to the challenges for describing blood flow in microchannels, including rheology of blood fluid, suspension features of red blood cells (RBCs), laminar hydrodynamic influence and effect of surface roughness. The analysis shows that due to the hyperelastic property of RBC and its comparable dimension with microchannels, blood fluid shows complex behaviours of two phase flow. The trajectory and migration of RBCs require accurate description of RBC deformation and interaction with plasma. Following on a discussion of modelling approaches, i.e. Eulerian method and Lagrangian method, the main stream modelling methods for multiphase flow are reviewed and their suitability to blood flow is analysed. It is concluded that the key issue for blood flow modelling is how to describe the suspended blood cells, modelled by Lagrangian method, and couple them with the based flow, modelled by Eulerian method. The multiphase flow methods are thereby classified based on the number of points required for describing a particle, as follows: (i) single-point particle methods, (ii) mutli-point particle methods, (iii) functional particle methods, and (iv) fluid particle methods. While single-point particle methods concentrate on particle dynamic movement, multipoint and functional particle methods can take into account particle mechanics and thus offer more detailed information for individual particles. Fluid particle methods provide good compromise between two phases, but require additional information for particle mechanics. For furthermore detailed description, we suggest to investigate the possibility using two domain coupling method, in which particles and base flow are modelled by two separated solvers. It is expected that this paper could clarify relevant issues in numerical modelling of blood flow in microchannels and induce some considerations for modelling blood flow using multiphase flow methods. © 2012 IEEE.

Modelling within-host spatiotemporal dynamics of invasive bacterial disease

Mechanistic determinants of bacterial growth, death, and spread within mammalian hosts cannot be fully resolved studying a single bacterial population. They are also currently poorly understood. Here, we report on the application of sophisticated experimental approaches to map spatiotemporal population dynamics of bacteria during an infection. We analyzed heterogeneous traits of simultaneous infections with tagged Salmonella enterica populations (wild-type isogenic tagged strains [WITS]) in wild-type and gene-targeted mice. WITS are phenotypically identical but can be distinguished and enumerated by quantitative PCR, making it possible, using probabilistic models, to estimate bacterial death rate based on the disappearance of strains through time. This multidisciplinary approach allowed us to establish the timing, relative occurrence, and immune control of key infection parameters in a true host-pathogen combination. Our analyses support a model in which shortly after infection, concomitant death and rapid bacterial replication lead to the establishment of independent bacterial subpopulations in different organs, a process controlled by host antimicrobial mechanisms. Later, decreased microbial mortality leads to an exponential increase in the number of bacteria that spread locally, with subsequent mixing of bacteria between organs via bacteraemia and further stochastic selection. This approach provides us with an unprecedented outlook on the pathogenesis of S. enterica infections, illustrating the complex spatial and stochastic effects that drive an infectious disease. The application of the novel method that we present in appropriate and diverse host-pathogen combinations, together with modelling of the data that result, will facilitate a comprehensive view of the spatial and stochastic nature of within-host dynamics. © 2008 Grant et al.