Explosion pressure prediction via polynomial mathematical correlation based on advanced CFD Modelling

Computational Fluid Dynamics CFD can be used as a powerful tool supporting engineers throughout the steps of the design. The combination of CFD with response surface methodology can play an important role in such cases. During the conceptual engineering design phase, a quick response is always a matter of urgency. During this phase even a sketch of the geometrical model is rare. Therefore, the utilisation of typical response surface developed for congested and confined environment rather than CFD can be an important tool to help the decision making process, when the geometrical model is not available, provided that similarities can be considered when taking into account the characteristic of the geometry in which the response surface was developed. The present work investigates how three different types of response surfaces behave when predicting overpressure in accidental scenarios based on CFD input. First order, partial second order and complete second order polynomial expressions are investigated. The predicted results are compared with CFD findings for a classical offshore experiment conducted by British Gas on behalf of Mobil and good agreement is observed for higher order response surfaces. The higher order response surface calculations are also compared with CFD calculations for a typical offshore module and good agreement is also observed. © 2011 Elsevier Ltd.

Optimal design of Functionally Graded Materials using a procedural model and Particle Swarm Optimization

A new method for the optimal design of Functionally Graded Materials (FGM) is proposed in this paper. Instead of using the widely used explicit functional models, a feature tree based procedural model is proposed to represent generic material heterogeneities. A procedural model of this sort allows more than one explicit function to be incorporated to describe versatile material gradations and the material composition at a given location is no longer computed by simple evaluation of an analytic function, but obtained by execution of customizable procedures. This enables generic and diverse types of material variations to be represented, and most importantly, by a reasonably small number of design variables. The descriptive flexibility in the material heterogeneity formulation as well as the low dimensionality of the design vectors help facilitate the optimal design of functionally graded materials. Using the nature-inspired Particle Swarm Optimization (PSO) method, functionally graded materials with generic distributions can be efficiently optimized. We demonstrate, for the first time, that a PSO based optimizer outperforms classical mathematical programming based methods, such as active set and trust region algorithms, in the optimal design of functionally graded materials. The underlying reason for this performance boost is also elucidated with the help of benchmarked examples. © 2011 Elsevier Ltd. All rights reserved.

The influence of particle shape on the stress-strain and creep response of a fine silica sand

The influence of particle shape on the stress-strain response of fine silica sand is investigated experimentally. Two sands from the same source and with the same particle size distribution were examined using Fourier descriptor analysis for particle shape. Their grains were, on average, found to have similar angularity but different elongation. During triaxial stress path testing, the stress-strain behavior of the sands for both loading and creep stages were found to be influenced by particle elongation. In particular, the behavior of the sand with less elongated grains was more like that of rounded glass beads during creep. The results highlight the role of particle shape in stress transmission in granular packings and suggest that shape should be taken more rigorously into consideration in characterizing geomaterials. © 2005 Taylor & Francis Group.

Statistical correlation between protein secondary structure and messenger RNA stem-loop structure

Anew integrated sequence-structure database, called IADE (Integrated ASTRAL-DSSP-EMBL), incorporating matching mRNA sequence, amino acid sequence, and protein secondary structural data, is constructed. It includes 648 protein domains. Based on the IADE database, we studied the relation between RNA stem-loop frequencies and protein secondary structure. It was found that the alpha-helices and beta-strands on proteins tend to be preferably "coded" by mRNA stem region, while the coils on proteins tend to be preferably "coded" by mRNA loop region. These tendencies are more obvious if we observe the structural words (SWs). An SW is defined by a four-amino-acid-fragment that shows the pronounced secondary structural (alpha-helix or beta-strand) propensity. It is demonstrated that the deduced correlation between protein and mRNA structure can hardly be explained as the stochastic fluctuation effect. (C) 2003 Wiley Periodicals, Inc.

Spatial correlation of heat release rate and sound emission from turbulent premixed flames

The two-point spatial correlation of the rate of change of fluctuating heat release rate is central to the sound emission from open turbulent flames, and a few attempts have been made to address this correlation in recent studies. In this paper, the two-point correlation and its role in combustion noise are studied by analysing direct numerical simulation (DNS) data of statistically multi-dimensional turbulent premixed flames. The results suggest that this correlation function depends on the separation distance and direction but, not on the positions inside the flame brush. This correlation can be modelled using a combination of Hermite-Gaussian functions of zero and second order, i.e. functions of the form (1-Ax2)e-Bx2 for constants A and B, to include its possible negative values. The integral correlation volume obtained using this model is about 0.2δL3 with the length scale obtained from its cube root being about 0.6δ L, where δ L is the laminar flame thermal thickness. Both of the values are slightly larger than the values reported in an earlier study because of the anisotropy observed for the correlation. This model together with the turbulence-dependent parameter K, the ratio of the root-mean-square (RMS) value of the rate of change of reaction rate to the mean reaction rate, derived from the DNS data is applied to predict the far-field sound emitted from open flames. The calculated noise levels agree well with recently reported measurements and show a sensitivity to K values. © 2012 The Combustion Institute.

Single-particle probing of edge-state formation in a graphene nanoribbon

We investigate the effect of a perpendicular magnetic field on the single-particle charging spectrum of a graphene quantum dot embedded inline with a nanoribbon. We observe uniform shifts in the single-particle spectrum which coincide with peaks in the magnetoconductance, implicating Landau level condensation and edge state formation as the mechanism underlying magnetic field-enhanced transmission through graphene nanostructures. The experimentally determined ratio of bulk to edge states is supported by single-particle band-structure simulations, while a fourfold beating of the Coulomb blockade transmission amplitude points to many-body interaction effects during Landau level condensation of the ν=0 state. © 2012 American Physical Society.

2D PIV measurements in the near field of grid turbulence using stitched fields from multiple cameras

We present measurements of grid turbulence using 2D particle image velocimetry taken immediately downstream from the grid at a Reynolds number of Re M = 16500 where M is the rod spacing. A long field of view of 14M x 4M in the down- and cross-stream directions was achieved by stitching multiple cameras together. Two uniform biplanar grids were selected to have the same M and pressure drop but different rod diameter D and crosssection. A large data set (10 4 vector fields) was obtained to ensure good convergence of second-order statistics. Estimations of the dissipation rate ε of turbulent kinetic energy (TKE) were found to be sensitive to the number of meansquared velocity gradient terms included and not whether the turbulence was assumed to adhere to isotropy or axisymmetry. The resolution dependency of different turbulence statistics was assessed with a procedure that does not rely on the dissipation scale η. The streamwise evolution of the TKE components and ε was found to collapse across grids when the rod diameter was included in the normalisation. We argue that this should be the case between all regular grids when the other relevant dimensionless quantities are matched and the flow has become homogeneous across the stream. Two-point space correlation functions at x/M = 1 show evidence of complex wake interactions which exhibit a strong Reynolds number dependence. However, these changes in initial conditions disappear indicating rapid cross-stream homogenisation. On the other hand, isotropy was, as expected, not found to be established by x/M = 12 for any case studied. © Springer-Verlag 2012.

A simple prediction model for asphalt surface texture incorporating mix gradation and air voids

This paper presents the results of a preliminary study that seeks to show how asphalt grading and air voids are related to the texture depth of asphalt. The fiftieth percentile particle size (D50) is shown to be a good predictor of texture depth measurements from a collected database of field and laboratory studies. The D50 is used to normalise collected texture data and this 'relative texture' is shown to correlate with air voids. Regression analyses confirm that air voids should be included along with a measure of gradation in the interpretation of asphalt surface texture.The derived formulae are used to develop correlation charts.

Acoustic radiation force of a Bessel beam on a porous sphere.

The possibility of using acoustic Bessel beams to produce an axial pulling force on porous particles is examined in an exact manner. The mathematical model utilizes the appropriate partial-wave expansion method in spherical coordinates, while Biot's model is used to describe the wave motion within the poroelastic medium. Of particular interest here is to examine the feasibility of using Bessel beams for (a) acoustic manipulation of fine porous particles and (b) suppression of particle resonances. To verify the viability of the technique, the radiation force and scattering form-function are calculated for aluminum and silica foams at various porosities. Inspection of the results has shown that acoustic manipulation of low porosity (<0.3) spheres is similar to that of solid elastic spheres, but this behavior significantly changes at higher porosities. Results have also shown a strong correlation between the backscattered form-function and the regions of negative radiation force. It has also been observed that the high-order resonances of the particle can be effectively suppressed by choosing the beam conical angle such that the acoustic contribution from that particular mode vanishes. This investigation may be helpful in the development of acoustic tweezers for manipulation of micro-porous drug delivery carrier and contrast agents.

The Gaussian mixture MCMC particle algorithm for dynamic cluster tracking

We present a novel filtering algorithm for tracking multiple clusters of coordinated objects. Based on a Markov chain Monte Carlo (MCMC) mechanism, the new algorithm propagates a discrete approximation of the underlying filtering density. A dynamic Gaussian mixture model is utilized for representing the time-varying clustering structure. This involves point process formulations of typical behavioral moves such as birth and death of clusters as well as merging and splitting. For handling complex, possibly large scale scenarios, the sampling efficiency of the basic MCMC scheme is enhanced via the use of a Metropolis within Gibbs particle refinement step. As the proposed methodology essentially involves random set representations, a new type of estimator, termed the probability hypothesis density surface (PHDS), is derived for computing point estimates. It is further proved that this estimator is optimal in the sense of the mean relative entropy. Finally, the algorithm's performance is assessed and demonstrated in both synthetic and realistic tracking scenarios. © 2012 Elsevier Ltd. All rights reserved.