Shock dynamics of random structures.

Predicting the response of a structure following an impact is of interest in situations where parts of a complex assembly may come into contact. Standard approaches are based on the knowledge of the impulse response function, requiring the knowledge of the modes and the natural frequencies of the structure. In real engineering structures the statistics of higher natural frequencies follows those of the Gaussian Orthogonal Ensemble, this allows the application of random point process theory to get a mean impulse response function by the knowledge of the modal density of the structure. An ensemble averaged time history for both the response and the impact force can be predicted. Once the impact characteristics are known in the time domain, a simple Fourier Transform allows the frequency range of the impact excitation to be calculated. Experimental and numerical results for beams, plates, and cylinders are presented to confirm the validity of the method.

Statistics and dynamics of turbulence-flame alignment in premixed combustion

The geometric alignment of turbulent strain-rate structures with premixed flames greatly influences the results of the turbulence-flame interaction. Here, the statistics and dynamics of this alignment are experimentally investigated in turbulent premixed Bunsen flames using high-repetition-rate stereoscopic particle image velocimetry. In all cases, the statistics showed that the most extensive principal strain-rate associated with the turbulence preferentially aligned such that it was more perpendicular than parallel to the flame surface normal direction. The mean turbulence-flame alignment differed between the flames, with the stronger flames (higher laminar flame speed) exhibiting stronger preferential alignment. Furthermore, the preferential alignment was greatest on the reactant side of the mean flame brush. To understand these differences, individual structures of fluid-dynamic strain-rate were tracked through time in a Lagrangian manner (i.e., by following the fluid elements). It was found that the flame surface affected the orientation of the turbulence structures, with the majority of structures rotating as they approached the flame such that their most extensive principal strain-rate was perpendicular to the flame normal. The maximum change in turbulent structure orientation was found to decrease with the strength of the structure, increase with the strength of the flame, and exhibit similar trends when the structure strength and flame strength were represented by a Karlovitz number. The mean change in orientation decreased from the unburnt to burnt side of the flame brush and appears to be influenced by the overall flame shape. © 2011 The Combustion Institute.

On Mixing and Shaking : Structure and Dynamics of Turbulent Stratified Flames

The drive for low emission combustion systems encourages applications using premixed flames. Yet in many applications, considerations of flame stability or mixing times lead to systems with neither premixed nor diffusion flames, which are often called technically premixed or stratified flames. In this talk we discuss the current state of understanding of the effect of mixing and extent of stratification on the structure, microstructure and dynamics of selected turbulent stratified flames. Over the past few years, a significant database of scalar and velocity data has been built to analyze the effects of unmixedness on local and global flame structure. Microscale studies of the flame structures show in detail how the effect of local stratification affects (or not!) the flame structure, flame surface density and scalar dissipation rates, and production of selected species. The experiments place exacting demands on current spectroscopic diagnostics, and reveal the progress and limits to our understanding of turbulent flames in general. The dynamics of stratified flames with respect to instabilities is also shown to be very rich, as the particular shape of the flames and the stabilization points are is significantly affected by the fuel distribution, modifying the rate and location of heat release, and thus the coupling with the surrounding acoustics and determining the onset of self-excitations.

Intracellular demography and the dynamics of Salmonella enterica infections.

An understanding of within-host dynamics of pathogen interactions with eukaryotic cells can shape the development of effective preventive measures and drug regimes. Such investigations have been hampered by the difficulty of identifying and observing directly, within live tissues, the multiple key variables that underlay infection processes. Fluorescence microscopy data on intracellular distributions of Salmonella enterica serovar Typhimurium (S. Typhimurium) show that, while the number of infected cells increases with time, the distribution of bacteria between cells is stationary (though highly skewed). Here, we report a simple model framework for the intensity of intracellular infection that links the quasi-stationary distribution of bacteria to bacterial and cellular demography. This enables us to reject the hypothesis that the skewed distribution is generated by intrinsic cellular heterogeneities, and to derive specific predictions on the within-cell dynamics of Salmonella division and host-cell lysis. For within-cell pathogens in general, we show that within-cell dynamics have implications across pathogen dynamics, evolution, and control, and we develop novel generic guidelines for the design of antibacterial combination therapies and the management of antibiotic resistance.

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.

Intracellular demography and the dynamics of Salmonella enterica infections.

An understanding of within-host dynamics of pathogen interactions with eukaryotic cells can shape the development of effective preventive measures and drug regimes. Such investigations have been hampered by the difficulty of identifying and observing directly, within live tissues, the multiple key variables that underlay infection processes. Fluorescence microscopy data on intracellular distributions of Salmonella enterica serovar Typhimurium (S. Typhimurium) show that, while the number of infected cells increases with time, the distribution of bacteria between cells is stationary (though highly skewed). Here, we report a simple model framework for the intensity of intracellular infection that links the quasi-stationary distribution of bacteria to bacterial and cellular demography. This enables us to reject the hypothesis that the skewed distribution is generated by intrinsic cellular heterogeneities, and to derive specific predictions on the within-cell dynamics of Salmonella division and host-cell lysis. For within-cell pathogens in general, we show that within-cell dynamics have implications across pathogen dynamics, evolution, and control, and we develop novel generic guidelines for the design of antibacterial combination therapies and the management of antibiotic resistance.