A study on the flow characteristics of an industrial radiant tube burner

The thesis presents an experimentally validated modelling study of the flow of combustion air in an industrial radiant tube burner (RTB). The RTB is used typically in industrial heat treating furnaces. The work has been initiated because of the need for improvements in burner lifetime and performance which are related to the fluid mechanics of the com busting flow, and a fundamental understanding of this is therefore necessary. To achieve this, a detailed three-dimensional Computational Fluid Dynamics (CFD) model has been used, validated with experimental air flow, temperature and flue gas measurements. Initially, the work programme is presented and the theory behind RTB design and operation in addition to the theory behind swirling flows and methane combustion. NOx reduction techniques are discussed and numerical modelling of combusting flows is detailed in this section. The importance of turbulence, radiation and combustion modelling is highlighted, as well as the numerical schemes that incorporate discretization, finite volume theory and convergence. The study first focuses on the combustion air flow and its delivery to the combustion zone. An isothermal computational model was developed to allow the examination of the flow characteristics as it enters the burner and progresses through the various sections prior to the discharge face in the combustion area. Important features identified include the air recuperator swirler coil, the step ring, the primary/secondary air splitting flame tube and the fuel nozzle. It was revealed that the effectiveness of the air recuperator swirler is significantly compromised by the need for a generous assembly tolerance. Also, there is a substantial circumferential flow maldistribution introduced by the swirier, but that this is effectively removed by the positioning of a ring constriction in the downstream passage. Computations using the k-ε turbulence model show good agreement with experimentally measured velocity profiles in the combustion zone and proved the use of the modelling strategy prior to the combustion study. Reasonable mesh independence was obtained with 200,000 nodes. Agreement was poorer with the RNG  k-ε and Reynolds Stress models. The study continues to address the combustion process itself and the heat transfer process internal to the RTB. A series of combustion and radiation model configurations were developed and the optimum combination of the Eddy Dissipation (ED) combustion model and the Discrete Transfer (DT) radiation model was used successfully to validate a burner experimental test. The previously cold flow validated k-ε turbulence model was used and reasonable mesh independence was obtained with 300,000 nodes. The combination showed good agreement with temperature measurements in the inner and outer walls of the burner, as well as with flue gas composition measured at the exhaust. The inner tube wall temperature predictions validated the experimental measurements in the largest portion of the thermocouple locations, highlighting a small flame bias to one side, although the model slightly over predicts the temperatures towards the downstream end of the inner tube. NOx emissions were initially over predicted, however, the use of a combustion flame temperature limiting subroutine allowed convergence to the experimental value of 451 ppmv. With the validated model, the effectiveness of certain RTB features identified previously is analysed, and an analysis of the energy transfers throughout the burner is presented, to identify the dominant mechanisms in each region. The optimum turbulence-combustion-radiation model selection was then the baseline for further model development. One of these models, an eccentrically positioned flame tube model highlights the failure mode of the RTB during long term operation. Other models were developed to address NOx reduction and improvement of the flame profile in the burner combustion zone. These included a modified fuel nozzle design, with 12 circular section fuel ports, which demonstrates a longer and more symmetric flame, although with limited success in NOx reduction. In addition, a zero bypass swirler coil model was developed that highlights the effect of the stronger swirling combustion flow. A reduced diameter and a 20 mm forward displaced flame tube model shows limited success in NOx reduction; although the latter demonstrated improvements in the discharge face heat distribution and improvements in the flame symmetry. Finally, Flue Gas Recirculation (FGR) modelling attempts indicate the difficulty of the application of this NOx reduction technique in the Wellman RTB. Recommendations for further work are made that include design mitigations for the fuel nozzle and further burner modelling is suggested to improve computational validation. The introduction of fuel staging is proposed, as well as a modification in the inner tube to enhance the effect of FGR.

Studies on the generalisation of Gaussian processes and Bayesian neural networks

The assessment of the reliability of systems which learn from data is a key issue to investigate thoroughly before the actual application of information processing techniques to real-world problems. Over the recent years Gaussian processes and Bayesian neural networks have come to the fore and in this thesis their generalisation capabilities are analysed from theoretical and empirical perspectives. Upper and lower bounds on the learning curve of Gaussian processes are investigated in order to estimate the amount of data required to guarantee a certain level of generalisation performance. In this thesis we analyse the effects on the bounds and the learning curve induced by the smoothness of stochastic processes described by four different covariance functions. We also explain the early, linearly-decreasing behaviour of the curves and we investigate the asymptotic behaviour of the upper bounds. The effect of the noise and the characteristic lengthscale of the stochastic process on the tightness of the bounds are also discussed. The analysis is supported by several numerical simulations. The generalisation error of a Gaussian process is affected by the dimension of the input vector and may be decreased by input-variable reduction techniques. In conventional approaches to Gaussian process regression, the positive definite matrix estimating the distance between input points is often taken diagonal. In this thesis we show that a general distance matrix is able to estimate the effective dimensionality of the regression problem as well as to discover the linear transformation from the manifest variables to the hidden-feature space, with a significant reduction of the input dimension. Numerical simulations confirm the significant superiority of the general distance matrix with respect to the diagonal one.In the thesis we also present an empirical investigation of the generalisation errors of neural networks trained by two Bayesian algorithms, the Markov Chain Monte Carlo method and the evidence framework; the neural networks have been trained on the task of labelling segmented outdoor images.

Pyrolysis liquids and gases as alternative fuels in internal combustion engines:a review

Liquids and gases produced through biomass pyrolysis have potential as renewable fuels to replace fossil fuels in conventional internal combustion engines. This review compares the properties of pyrolysis fuels, produced from a variety of feedstocks and using different pyrolysis techniques, against those of fossil fuels. High acidity, the presence of solid particles, high water content, high viscosity, storage and thermal instability, and low energy content are typical characteristics of pyrolysis liquids. A survey of combustion, performance and exhaust emission results from the use of pyrolysis liquids (both crude and up-graded) in compression ignition engines is presented. With only a few exceptions, most authors have reported difficulties associated with the adverse properties of pyrolysis liquids, including: corrosion and clogging of the injectors, long ignition delay and short combustion duration, difficulty in engine start-up, unstable operation, coking of the piston and cylinders and subsequent engine seizure. Pyrolysis gas can be used more readily, either in spark ignition or compression ignition engines; however, NO reduction techniques are desirable. Various approaches to improve the properties of pyrolysis liquids are discussed and a comparison of the properties of up-graded vs. crude pyrolysis liquid is included. Further developments in up-gradation techniques, such as hydrocracking and bio-refinery approaches, could lead to the production of green diesel and green gasoline. Modifications required to engines for use with pyrolysis liquids, for example in the fuel supply and injection systems, are discussed. Storage stability and economic issues are also reviewed. Our study presents recent progress and important R&D areas for successful future use of pyrolysis fuels in internal combustion engines.

Highly photosensitive polymethyl methacrylate microstructured polymer optical fiber with doped core

In this Letter, we report the fabrication of a highly photosensitive, microstructured polymer optical fiber using benzyl dimethyl ketal as a dopant, as well as the inscription of a fiber Bragg grating in the fiber. A refractive index change in the core of at least 3.2 × 10 has been achieved, providing a grating with a strong transmission rejection of -23 dB with an inscription time of only 13 min. The fabrication method has a big advantage compared to doping step index fiber since it enables doping of the fiber without using extra dopants to compensate for the index reduction in the core introduced by the photosensitive agent. © 2013 Optical Society of America.

Visualisation and browsing of image databases

In this chapter we provide a comprehensive overview of the emerging field of visualising and browsing image databases. We start with a brief introduction to content-based image retrieval and the traditional query-by-example search paradigm that many retrieval systems employ. We specify the problems associated with this type of interface, such as users not being able to formulate a query due to not having a target image or concept in mind. The idea of browsing systems is then introduced as a means to combat these issues, harnessing the cognitive power of the human mind in order to speed up image retrieval.We detail common methods in which the often high-dimensional feature data extracted from images can be used to visualise image databases in an intuitive way. Systems using dimensionality reduction techniques, such as multi-dimensional scaling, are reviewed along with those that cluster images using either divisive or agglomerative techniques as well as graph-based visualisations. While visualisation of an image collection is useful for providing an overview of the contained images, it forms only part of an image database navigation system. We therefore also present various methods provided by these systems to allow for interactive browsing of these datasets. A further area we explore are user studies of systems and visualisations where we look at the different evaluations undertaken in order to test usability and compare systems, and highlight the key findings from these studies. We conclude the chapter with several recommendations for future work in this area. © 2011 Springer-Verlag Berlin Heidelberg.

CO2 emissions reduction of Chinese light manufacturing industries:a novel RAM-based global Malmquist-Luenberger productivity index

Climate change has become one of the most challenging issues facing the world. Chinese government has realized the importance of energy conservation and prevention of the climate changes for sustainable development of China's economy and set targets for CO2 emissions reduction in China. In China industry contributes 84.2% of the total CO2 emissions, especially manufacturing industries. Data envelopment analysis (DEA) and Malmquist productivity (MP) index are the widely used mathematical techniques to address the relative efficiency and productivity of a group of homogenous decision making units, e.g. industries or countries. However, in many real applications, especially those related to energy efficiency, there are often undesirable outputs, e.g. the pollutions, waste and CO2 emissions, which are produced inevitably with desirable outputs in the production. This paper introduces a novel Malmquist-Luenberger productivity (MLP) index based on directional distance function (DDF) to address the issue of productivity evolution of DMUs in the presence of undesirable outputs. The new RAM (Range-adjusted measure)-based global MLP index has been applied to evaluate CO2 emissions reduction in Chinese light manufacturing industries. Recommendations for policy makers have been discussed.

Evaluating the performance of a EuroDivisia index using artificial intelligence techniques

We compare two methods in order to predict inflation rates in Europe. One method uses a standard back propagation neural network and the other uses an evolutionary approach, where the network weights and the network architecture is evolved. Results indicate that back propagation produces superior results. However, the evolving network still produces reasonable results with the advantage that the experimental set-up is minimal. Also of interest is the fact that the Divisia measure of money is superior as a predictive tool over simple sum.

Evaluating the performance of a EuroDivisia index using artificial intelligence techniques

This paper compares two methods to predict in°ation rates in Europe. One method uses a standard back propagation neural network and the other uses an evolutionary approach, where the network weights and the network architecture are evolved. Results indicate that back propagation produces superior results. However, the evolving network still produces reasonable results with the advantage that the experimental set-up is minimal. Also of interest is the fact that the Divisia measure of money is superior as a predictive tool over simple sum.

Systemic reduction in glutathione levels occurs in patients with primary open-angle glaucoma

PURPOSE. To assess the level of plasma glutathione in patients with untreated primary open-angle glaucoma. METHODS. Twenty-one patients with newly diagnosed primary open-angle glaucoma and 34 age- and gender-matched control subjects were subjected to a blood analysis to detect the level of circulating glutathione in its reduced and oxidized forms. The effect of age, gender, and systemic blood pressure on circulating glutathione levels was also analyzed. RESULTS. Age had a negative effect on the level of both reduced and total glutathione (P = 0.002, r = -0.52 and P = 0.002, r = -0.52, respectively) in control subjects but not in patients with glaucoma (P > 0.05, r = 0.27, and P > 0.05, r = 0.22, respectively). In the control group, men demonstrated higher levels of both reduced and total glutathione than did women (P = 0.024 and P = 0.032, respectively). After correction for age and gender influences on blood glutathione levels, patients with glaucoma exhibited significantly lower levels of reduced and total glutathione than did control subjects (P = 0.010, F = 7.24 and P = 0.006, F = 8.38, respectively). No differences between study groups were observed in either oxidized glutathione levels or redox index (P > 0.05, F = 0.50; and P > 0.05, F = 0.30, respectively). CONCLUSIONS. Patients with glaucoma exhibit low levels of circulating glutathione, suggesting a general compromise of the antioxidative defense. Copyright © Association for Research in Vision and Ophthalmology.

Evaluation of routine microbiological techniques for establishing the diagnosis of catheter-related bloodstream infection caused by coagulase-negative staphylococci

Microbiological diagnosis of catheter-related bloodstream infection (CR-BSI) is often based on isolation of indistinguishable micro-organisms from an explanted catheter tip and blood culture, confirmed by antibiograms. Whether phenotypic identification of coagulase-negative staphylococci (CoNS) allows an accurate diagnosis of CR-BSI to be established was evaluated. Eight patients with a diagnosis of CR-BSI had CoNS isolated from pure blood cultures and explanted catheter tips which were considered as indistinguishable strains by routine microbiological methods. For each patient, an additional three colonies of CoNS isolated from the blood and five from the catheter tip were subcultured and further characterized by antibiogram profiles, analytical profile index (API) biotyping and PFGE. PFGE distinguished more strains of CoNS compared to API biotyping or antibiograms (17, 10 and 11, respectively). By PFGE, indistinguishable micro-organisms were only isolated from pure blood and catheter tip cultures in four out of eight (50%) patients thus supporting the diagnosis of CR-BSI. In another patient, indistinguishable micro-organisms were identified in both cultures; however, other strains of CoNS were also present. The remaining three patients had multiple strains of CoNS, none of which were indistinguishable in the tip and blood cultures, thus questioning the diagnosis of CR-BSI. Phenotypic characterization of CoNS lacked discriminatory power. Current routine methods of characterizing a limited number of pooled colonies may generate misleading results as multiple strains may be present in the cultures. Multiple colonies should be studied using a rapid genotypic characterization method to confirm or refute the diagnosis of CR-BSI. © 2007 SGM.

Response-based segmentation using Finite Mixture Partial Least Squares: theoretical foundations and an application to American Customer Satisfaction Index Data

When applying multivariate analysis techniques in information systems and social science disciplines, such as management information systems (MIS) and marketing, the assumption that the empirical data originate from a single homogeneous population is often unrealistic. When applying a causal modeling approach, such as partial least squares (PLS) path modeling, segmentation is a key issue in coping with the problem of heterogeneity in estimated cause-and-effect relationships. This chapter presents a new PLS path modeling approach which classifies units on the basis of the heterogeneity of the estimates in the inner model. If unobserved heterogeneity significantly affects the estimated path model relationships on the aggregate data level, the methodology will allow homogenous groups of observations to be created that exhibit distinctive path model estimates. The approach will, thus, provide differentiated analytical outcomes that permit more precise interpretations of each segment formed. An application on a large data set in an example of the American customer satisfaction index (ACSI) substantiates the methodology’s effectiveness in evaluating PLS path modeling results.

Bio-inspired carbon electro-catalysis for the oxygen reduction reaction

We report the synthesis, characterisation and catalytic performance of two nature-inspired biomass-derived electro-catalysts for the oxygen reduction reaction in fuel cells. The catalysts were prepared via pyrolysis of a real food waste (lobster shells) or by mimicking the composition of lobster shells using chitin and CaCO3 particles followed by acid washing. The simplified model of artificial lobster was prepared for better reproducibility. The calcium carbonate in both samples acts as a pore agent, creating increased surface area and pore volume, though considerably higher in artificial lobster samples due to the better homogeneity of the components. Various characterisation techniques revealed the presence of a considerable amount of hydroxyapatite left in the real lobster samples after acid washing and a low content of carbon (23%), nitrogen and sulphur (<1%), limiting the surface area to 23 m2/g, and consequently resulting in rather poor catalytic activity. However, artificial lobster samples, with a surface area of ≈200 m2/g and a nitrogen doping of 2%, showed a promising onset potential, very similar to a commercially available platinum catalyst, with better methanol tolerance, though with lower stability in long time testing over 10,000 s.

Advanced fibre gratings and their applications

This thesis describes a detailed study of advanced fibre grating devices using Bragg (FBG) and long-period (LPG) structures and their applications in optical communications and sensing. The major contributions presented in this thesis are summarised below. One of the most important contributions from the research work presented in this thesis is a systematic theoretical study of many distinguishing structures of fibre gratings. Starting from the Maxwell equations, the coupled-mode equations for both FBG and LPG were derived and the mode-overlap factor was analytically discussed. Computing simulation programmes utilising matrix transform method based on the models built upon the coupled-mode equations were developed, enabling simulations of spectral response in terms of reflectivity, bandwidth, sidelobes and dispersion of gratings of different structures including uniform and chirped, phase-shifted, Moiré, sampled Bragg gratings, phase-shifted and cascaded long-period gratings. Although the majority of these structures were modelled numerically, analytical expressions for some complex structures were developed with a clear physical picture. Several apodisation functions were proposed to improve sidelobe suppression, which guided effective production of practical devices for demanding applications. Fibre grating fabrication is the other major part involved in the Ph.D. programme. Both the holographic and scan-phase-mask methods were employed to fabricate Bragg and long-period gratings of standard and novel structures. Significant improvements were particularly made in the scan-phase-mask method to enable the arbitrarily tailoring of the spectral response of grating devices. Two specific techniques - slow-shifting and fast-dithering the phase-mask implemented by a computer controlled piezo - were developed to write high quality phase-shifted, sampled and apodised gratings. A large number of LabVIEW programmes were constructed to implement standard and novel fabrication techniques. In addition, some fundamental studies of grating growth in relating to the UV exposure and hydrogenation induced index were carried out. In particular, Type IIa gratings in non-hydrogenated B/Ge co-doped fibres and a re-generated grating in hydrogenated B/Ge fibre were investigated, showing a significant observation of thermal coefficient reduction. Optical sensing applications utilising fibre grating devices form the third major part of the research work presented in this thesis. Several experiments of novel sensing and sensing-demodulating were implemented. For the first time, an intensity and wavelength dual-coding interrogation technique was demonstrated showing significantly enhanced capacity of grating sensor multiplexing. Based on the mode-splitting measurement, instead of using conventional wavelength-shifting detection technique, successful demonstrations were also made for optical load and bend sensing of ultra-high sensitivity employing LPG structures. In addition, edge-filters and low-loss high-rejection bandpass filters of 50nm stop-band were fabricated for application in optical sensing and high-speed telecommunication systems

The production of the enzyme dextransucrase by batch and continuous fermentation techniques

A review of the literature of work carried out on dextransucrase production, purification, immobilization and reactions has been carried out. A brief review has also been made of the literature concerning general enzyme biotechnology and fermentation technology. Fed-batch fermentation of the bacteria Leuconostoc mesenteroides NRRL B512 (F) to produce dextransucrase has formed the major part of this research. Aerobic and anaerobic fermentations have been studied using a 16 litre New Brunswick fermenter which has a 3-12 litre working volume. The initial volume of broth used in the studies was 6 litres. The results of the fed-batch fermentations showed for the first time that yields of dextransucrase are much higher under the anaerobic conditions than during the aerobic fermentations. Dextransucrase containing 300-350 DSU/cm3 of enzyme activity has been obtained during the aerobic fermentations, while in the anaerobic fermentations, enzyme yields containing 450-500 DSU/cm3 have been obtained routinely. The type of yeast extract used in the fermentation medium has been found to have significant effects on enzyme yield. Of the different types studied, the Gistex Standard was found to be the type that favoured the highest enzyme production. Studies have also been carried out on the effect of agitation rate and antifoam on the enzyme production during the anaerobic experiments. Agitation rates of up to 600 rpm were found not to affect the enzyme yield, however, the presence of antifoam in the medium led to a significant reduction in enzyme activity (less than 300 DSU/cm3). Scale-up of the anaerobic fermentations has been performed at up to the 1000 litre level with enzyme yields containing more than 400 DSU/cm3 of activity being produced. Some of the enzyme produced at this scale was used for the first time to produce dextran on an industrial scale via the enzyme route, with up to 99% conversion of sucrose to dextran being obtained. An attempt has been made at continuous dextransucrase production. Cell washout was observed to occur at dilution rates of greater than 0.4 h-1. Dextransucrase containing up to 25 DSU/cm3/h has been produced continuously.

Exploratory database visualisation: the application and assessment of data and dimensionality reduction

This thesis describes the development of a complete data visualisation system for large tabular databases, such as those commonly found in a business environment. A state-of-the-art 'cyberspace cell' data visualisation technique was investigated and a powerful visualisation system using it was implemented. Although allowing databases to be explored and conclusions drawn, it had several drawbacks, the majority of which were due to the three-dimensional nature of the visualisation. A novel two-dimensional generic visualisation system, known as MADEN, was then developed and implemented, based upon a 2-D matrix of 'density plots'. MADEN allows an entire high-dimensional database to be visualised in one window, while permitting close analysis in 'enlargement' windows. Selections of records can be made and examined, and dependencies between fields can be investigated in detail. MADEN was used as a tool for investigating and assessing many data processing algorithms, firstly data-reducing (clustering) methods, then dimensionality-reducing techniques. These included a new 'directed' form of principal components analysis, several novel applications of artificial neural networks, and discriminant analysis techniques which illustrated how groups within a database can be separated. To illustrate the power of the system, MADEN was used to explore customer databases from two financial institutions, resulting in a number of discoveries which would be of interest to a marketing manager. Finally, the database of results from the 1992 UK Research Assessment Exercise was analysed. Using MADEN allowed both universities and disciplines to be graphically compared, and supplied some startling revelations, including empirical evidence of the 'Oxbridge factor'.