Application of CFD to model fast pyrolysis of biomass

The article deals with the CFD modelling of fast pyrolysis of biomass in an Entrained Flow Reactor (EFR). The Lagrangian approach is adopted for the particle tracking, while the flow of the inert gas is treated with the standard Eulerian method for gases. The model includes the thermal degradation of biomass to char with simultaneous evolution of gases and tars from a discrete biomass particle. The chemical reactions are represented using a two-stage, semi-global model. The radial distribution of the pyrolysis products is predicted as well as their effect on the particle properties. The convective heat transfer to the surface of the particle is computed using the Ranz-Marshall correlation.

The impact of architecture on the performance of artificial neural networks

A number of researchers have investigated the impact of network architecture on the performance of artificial neural networks. Particular attention has been paid to the impact on the performance of the multi-layer perceptron of architectural issues, and the use of various strategies to attain an optimal network structure. However, there are still perceived limitations with the multi-layer perceptron and networks that employ a different architecture to the multi-layer perceptron have gained in popularity in recent years, particularly, networks that implement a more localised solution, where the solution in one area of the problem space does not impact, or has a minimal impact, on other areas of the space. In this study, we discuss the major architectural issues affecting the performance of a multi-layer perceptron, before moving on to examine in detail the performance of a new localised network, namely the bumptree. The work presented here examines the impact on the performance of artificial neural networks of employing alternative networks to the long established multi-layer perceptron. In particular, networks that impose a solution where the impact of each parameter in the final network architecture has a localised impact on the problem space being modelled are examined. The alternatives examined are the radial basis function and bumptree neural networks, and the impact of architectural issues on the performance of these networks is examined. Particular attention is paid to the bumptree, with new techniques for both developing the bumptree structure and employing this structure to classify patterns being examined.

Design of a flat-top fiber Bragg filter via quasi-random modulation of the refractive index

The statistics of the reflection spectrum of a short-correlated disordered fiber Bragg grating are studied. The averaged spectrum appears to be flat inside the bandgap and has significantly suppressed sidelobes compared to the uniform grating of the same bandwidth. This is due to the Anderson localization of the modes of a disordered grating. This observation prompts a new algorithm for designing passband reflection gratings. Using the stochastic invariant imbedding approach it is possible to obtain the probability distribution function for the random reflection coefficient inside the bandgap and obtain both the variance of the averaged reflectivity as well as the distribution of the time delay of the grating.

Effects of rare-earth co-doping on the local structure of rare-earth phosphate glasses using high and low energy X-ray diffraction

Rare-earth co-doping in inorganic materials has a long-held tradition of facilitating highly desirable optoelectronic properties for their application to the laser industry. This study concentrates specifically on rare-earth phosphate glasses, (R2O3)x(R'2O3)y(P2O5)1-(x+y), where (R, R') denotes (Ce, Er) or (La, Nd) co-doping and the total rare-earth composition corresponds to a range between metaphosphate, RP3O9, and ultraphosphate, RP5O14. Thereupon, the effects of rare-earth co-doping on the local structure are assessed at the atomic level. Pair-distribution function analysis of high-energy X-ray diffraction data (Qmax = 28 Å-1) is employed to make this assessment. Results reveal a stark structural invariance to rare-earth co-doping which bears testament to the open-framework and rigid nature of these glasses. A range of desirable attributes of these glasses unfold from this finding; in particular, a structural simplicity that will enable facile molecular engineering of rare-earth phosphate glasses with 'dial-up' lasing properties. When considered together with other factors, this finding also demonstrates additional prospects for these co-doped rare-earth phosphate glasses in nuclear waste storage applications. This study also reveals, for the first time, the ability to distinguish between P-O and PO bonding in these rare-earth phosphate glasses from X-ray diffraction data in a fully quantitative manner. Complementary analysis of high-energy X-ray diffraction data on single rare-earth phosphate glasses of similar rare-earth composition to the co-doped materials is also presented in this context. In a technical sense, all high-energy X-ray diffraction data on these glasses are compared with analogous low-energy diffraction data; their salient differences reveal distinct advantages of high-energy X-ray diffraction data for the study of amorphous materials. © 2013 The Owner Societies.

Multiscale molecular dynamics/hydrodynamics implementation of two dimensional “Mercedes Benz” water model

A multiscale Molecular Dynamics/Hydrodynamics implementation of the 2D Mercedes Benz (MB or BN2D) [1] water model is developed and investigated. The concept and the governing equations of multiscale coupling together with the results of the two-way coupling implementation are reported. The sensitivity of the multiscale model for obtaining macroscopic and microscopic parameters of the system, such as macroscopic density and velocity fluctuations, radial distribution and velocity autocorrelation functions of MB particles, is evaluated. Critical issues for extending the current model to large systems are discussed.

Individual variability analysis of fluorescence parameters measured in skin with different levels of nutritive blood flow

Fluorescence spectroscopy has recently become more common in clinical medicine. However, there are still many unresolved issues related to the methodology and implementation of instruments with this technology. In this study, we aimed to assess individual variability of fluorescence parameters of endogenous markers (NADH, FAD, etc.) measured by fluorescent spectroscopy (FS) in situ and to analyse the factors that lead to a significant scatter of results. Most studied fluorophores have an acceptable scatter of values (mostly up to 30%) for diagnostic purposes. Here we provide evidence that the level of blood volume in tissue impacts FS data with a significant inverse correlation. The distribution function of the fluorescence intensity and the fluorescent contrast coefficient values are a function of the normal distribution for most of the studied fluorophores and the redox ratio. The effects of various physiological (different content of skin melanin) and technical (characteristics of optical filters) factors on the measurement results were additionally studied.The data on the variability of the measurement results in FS should be considered when interpreting the diagnostic parameters, as well as when developing new algorithms for data processing and FS devices.