Oscillatory sensitivity patterns for global modes in wakes

Globally unstable wakes with co-flow at intermediate Reynolds numbers are studied, to quantify important spatial regions for the development and control of the global instability. One region of high structural sensitivity is found close to the inlet for all wakes, in agreement with previous findings for cylinder wakes. A second, elongated region of high structural sensitivity is seen downstream of the first one for unconfined wakes at Re = 400. When base flow modifications are considered, a spatially oscillating sensitivity pattern is found inside the downstream high structural sensitivity region. This implies that the same change in the base flow can either destabilize or stabilize the flow, depending on the exact position where it is applied. It is shown that the sensitivity pattern remains unchanged for different choices of streamwise boundary conditions and numerical resolution. Actual base flow modifications are applied in selected configurations, and the linear global modes recomputed. It is confirmed that the linear global eigenvalues move according to the predicted sensitivity pattern for small amplitude base flow modifications, for which the theory applies. We also look at the implications of a small control cylinder on the flow. Only the upstream high sensitivity region proves to be robust in terms of control, but one should be careful not to disturb the flow in the downstream high sensitivity region, in order to achieve control. The findings can have direct implications on the numerical resolution requirements for wakes at higher Reynolds numbers. Furthermore, they provide one more possible explanation to why confined wakes have a more narrow frequency spectrum than unconfined wakes.

Low-order modelling of ducted flames with temporally varying equivalence ratio in realistic geometries

The interaction between unsteady heat release and acoustic pressure oscillations in gas turbines results in self-excited combustion oscillations which can potentially be strong enough to cause significant structural damage to the combustor. Correctly predicting the interaction of these processes, and anticipating the onset of these oscillations can be difficult. In recent years much research effort has focused on the response of premixed flames to velocity and equivalence ratio perturbations. In this paper, we develop a flame model based on the socalled G-Equation, which captures the kinematic evolution of the flame surfaces, under the assumptions of axisymmetry, and ignoring vorticity and compressibility. This builds on previous work by Dowling [1], Schuller et al. [2], Cho & Lieuwen [3], among many others, and extends the model to a realistic geometry, with two intersecting flame surfaces within a non-uniform velocity field. The inputs to the model are the free-stream velocity perturbations, and the associated equivalence ratio perturbations. The model also proposes a time-delay calculation wherein the time delay for the fuel convection varies both spatially and temporally. The flame response from this model was compared with experiments conducted by Balachandran [4, 5], and found to show promising agreement with experimental forced case. To address the primary industrial interest of predicting self-excited limit cycles, the model has then been linked with an acoustic network model to simulate the closed-loop interaction between the combustion and acoustic processes. This has been done both linearly and nonlinearly. The nonlinear analysis is achieved by applying a describing function analysis in the frequency domain to predict the limit cycle, and also through a time domain simulation. In the latter case, the acoustic field is assumed to remain linear, with the nonlinearity in the response of the combustion to flow and equivalence ratio perturbations. A transfer function from unsteady heat release to unsteady pressure is obtained from a linear acoustic network model, and the corresponding Green function is used to provide the input to the flame model as it evolves in the time domain. The predicted unstable frequency and limit cycle are in good agreement with experiment, demonstrating the potential of this approach to predict instabilities, and as a test bench for developing control strategies. Copyright © 2011 by ASME.

Identifying cancer subtypes in glioblastoma by combining genomic, transcriptomic and epigenomic data

We present a nonparametric Bayesian method for disease subtype discovery in multi-dimensional cancer data. Our method can simultaneously analyse a wide range of data types, allowing for both agreement and disagreement between their underlying clustering structure. It includes feature selection and infers the most likely number of disease subtypes, given the data. We apply the method to 277 glioblastoma samples from The Cancer Genome Atlas, for which there are gene expression, copy number variation, methylation and microRNA data. We identify 8 distinct consensus subtypes and study their prognostic value for death, new tumour events, progression and recurrence. The consensus subtypes are prognostic of tumour recurrence (log-rank p-value of $3.6 \times 10^{-4}$ after correction for multiple hypothesis tests). This is driven principally by the methylation data (log-rank p-value of $2.0 \times 10^{-3}$) but the effect is strengthened by the other 3 data types, demonstrating the value of integrating multiple data types. Of particular note is a subtype of 47 patients characterised by very low levels of methylation. This subtype has very low rates of tumour recurrence and no new events in 10 years of follow up. We also identify a small gene expression subtype of 6 patients that shows particularly poor survival outcomes. Additionally, we note a consensus subtype that showly a highly distinctive data signature and suggest that it is therefore a biologically distinct subtype of glioblastoma. The code is available from https://sites.google.com/site/multipledatafusion/

Acoustic optimization of ultra-low count bypass outlet guide vanes

An optimization process has been used to design an ultra-low count fan outlet guide vane with an unconventional leading edge profile to reduce the interaction noise. Computational fluid dynamics has been used to predict the aerodynamic and acoustic performance of the stator vane. The final stator design has been built and tested in a representative fan stage rig to determine its tone noise characteristics. The stator vane is found to give significant tone noise reduction at the fundamental blade passing frequency at cut-back in line with design expectations. Detailed comparisons of predicted circumferential and radial modes levels against measured mode detection data are also presented. A good agreement was found between numerical predictions and experimental data.

Biofunctionalization of PET/SiO2 surfaces for single molecule experiments and medical applications

PET/SiO2 layers were chemically modified to maintain immobilization of functional single molecules. GFP molecules provide an ideal system due to their stability and intrinsic fluorescence. GFP in vivo biotinylated within its NH2-terminal region and attached on the substrate via the biotinstreptavidin bond was further investigated with confocal microscopy, atomic force microscopy (AFM) and spectroscopic ellipsometry (SE). AFM revealed monolayered donut-like structures representing assemblies of biotinstreptavidinbiotinGFP immobilized onto PET/SiO2 surfaces via mPEG. In particular, regions with an approximate height of 12 nm, which approaches the molecular dimensions of the above complex given by molecular modeling, could be detected. The dimensions of the donut-like structures suggest a close-to-each-other positioning of the GFP molecules - which, however, retain their functionality, as evidenced by confocal microscopy. © 2011 World Scientific Publishing Company.