The electronic nose is a device developed to mimic the human olfactory system. Despite raising interest from applications in the field of medicine, quality control, environmental control and security, such devices remain inferior to their biological counterparts. As the biological system is explored further, new discoveries generate new ways of thinking in creating electronic nose devices. This has led to a large variety of sensors and devices, all of which produce data that requires processing. The data are processed to extract information that can be used to classify or quantify the input to the electronic nose. However, as the devices have advanced, the data processing techniques have remained relatively static, refinements of established statistical methods. Recently, investigation into the phenomenon of nasal chromatography has brought about the development of a new class of electronic nose device; the artificial olfactory mucosa. Taking advantage of a retentive effect, inspired by the aqueous mucous layer covering the olfactory epithelium, this new device produces data whose spatio-temporal properties have not been seen in the field of chemical sensing before. Thus there is a need to develop new processing approaches to obtain the information being produced by these new devices. In this thesis, a new processing approach is presented, centred on the use of convolution to produce characteristic signals which contain information arising from a sensor space that is separated both spatially and temporally, realised in the form of multiple sensor arrays separated by retentive columns or channels. This combined signal is then used to extract an information rich feature set that can be passed on to classifiers or quantifiers to make practical use of the data. This method is simulated on data collected during the development of the artificial olfactory mucosa to validate its use, and then applied to several sets of real world data, collected from a variety of devices; from current e-nose technologies to newly developed artificial olfactory mucosa devices. The simulations put the device in very noisy conditions and the processing approach deals well with a high level of noise in most circumstances, its performance only deteriorating in the presence of extremely high levels of sensor drift. However, it is shown that this method not only has validity when dealing with the advanced devices for which it is intended, but also shows an improvement over standard processing approaches when utilised in conjunction with current technologies. Utilising convolution on data collected from current devices, methods are developed where the characteristic signal can be generated internally from a single array, and when applied, produce improvements over standard processing approaches.

The aim of this thesis is to develop a comprehensive mathematical model with detailed kinetics of Fischer-Tropsch (FT) and water gas shift reactions (WGS) to predict the results obtained from experimental study of cobalt-based FT synthesis conducted in a fixed-bed reactor. The kinetics’ parameters were evaluated for developed kinetics’ models, using an advanced optimization technique. Physical and statistical consistencies of the kinetics’ parameters were evaluated by various statistical methods. The developed model based on combination of alkyl/alkenyl mechanism (for production of n-paraffins and α-olefins) along with formate mechanism for WGS reaction provided the most accurate predictions. Model validation was conducted subsequent to completion of model calibration and estimation of proper kinetic parameters to ensure that model provides robust and realistic assessment of all parameters. Parametric studies were performed to investigate effects of operating conditions on the catalytic performance of FT synthesis with respect to products’ selectivities and syngas conversion. The operating conditions that have most significant effects were included in multi-objective optimization process using non-dominated sorting genetic algorithm to optimize selectivities and conversion. Pareto-front solutions can be used as dynamic database depending on specific requirement. Different operating condition can be selected from such database which privileges optimization of particular output.

The research topic addressed in this thesis is the development of new ideas and techniques for acceleration and automation of processes involved in the design of chemical products with predefined properties. In particular, we demonstrate techniques that address the shortcomings of the existing methods and take a bird's-eye view over the new possible directions for chemical product development necessitated by the integration of bio-feedstocks into the existing supply chain. Futhermore, we introduce an approach for sequential, on-line multi-target product/process optimization in a scenario where: automation of the overall design process is sought; adequate physical models are not available; unknown constraints on the decision space may be present; and resources are limited or costly. We test the approach on a number of simulations. The results indicate that the approach is able to, in a modest number of iterations, find solutions associated with the targets to a satisfactory degree of accuracy. In addition, for supervised problems where categorical data are available, we introduce an approach that allows one to perform categorization of a given product composition according to a particular property. We test our solutions empirically on real data. The results show that the approach compares well with existing state of the art techniques. We also investigate the application of a variety of nonlinear dimensionality techniques to the visualisation of chemical product data.

The main objective of this thesis is to develop relatively simple but reasonable engineering models within a CFD software framework to simulate fire in a compartment and fire growth and propagation in enclosures in which solid combustibles are involved through wall or ceiling linings. Gas phase combustion, radiation and solid fuel combustion are addressed in this study. At the heart of this study is the integration of the three sub-models representing the key elements mentioned above in compartment fire development and other auxiliary calculations such as the evaluation of the radiative properties of gas-soot mixture, temperature calculation for non-burning solid surfaces, etc. into a complete fire spread model. Shortcomings in the conventional six-flux radiation model are highlighted. These were demonstrated through a simple artificial test case and corrected in the modified six-flux model. The computational cost and accuracy of the six-flux model and the discrete transfer method (DTM) using different number of rays are also investigated. A simple empirical soot model is developed based on experimental observations that soot formation occurs in the fuel rich side of the chemical reaction region and the highest soot concentration is found in the same region. The soot model is important to evaluate the radiative properties of the gas-soot mixture in fires. By incorporating the gas-phase combustion model, the radiation models and the soot model, substantial improvement in the predicted upper layer temperature profiles is achieved in the simulations of one of the Steckler's room fire test. It is found that radiation plays an important, perhaps dominant role in creating the nearly uniform temperature distribution in the upper layer. The integral method to calculate temperatures of non-combustible solids is extended to be capable of dealing with the non-linearity of the reradiation at the solid surface(top surface) exposed to a fire and the convective heat loss at the opposite surface. The integral method is economic and simple for the calculation of temperatures of non-combustible solids. Pyrolysis models for nonchaning and charring solid combustibles are developed. The mass loss rates produced by the noncharring model for PMMA are in excellent agreement with experimental data. The charring model produced predictions for the mass loss rates and temperature distribution of a wood sample in very close agreement to that measured. Finally, qualitative and quantitative verifications for the integrated fire spread model are carried out. The model is demonstrated to be capable of both qualitatively and quantitatively predicting fire, fire growth and development within compartment fire scenarios.

In this thesis we describe the complex array of behaviours of a homogeneous thermotropic nematic liquid crystal in the context of a Landau-de Gennes theory. There exist two parameters that control the behaviour of the system: the temperature and the shear rate, and by employing continuation and bifurcation theory we describe the different time dependent states for the two and three dimensional cases. For the two dimensional case we compute the steady state solution branches finding that the flow favours an in-plane nematic state at higher temperatures, while at lower temperatures it favours a nematic state with preferred direction of alignment perpendicular to the shear plane, the so-called log-rolling state. We have found excellent agreement between the numerical calculations and analytical results in the limit of very low and very large values of the shear rate. The existence of a Takens-Bogdanov bifurcation in the underlying bifurcation diagram organises the steady and the time dependent solutions in the state diagram. The periodic orbits can be either of the wagging type, at intermediate values of the shear rate or of the tumbling type at lower shear rates. We complete the analysis of the two dimensional case, by considering a general planar flow and studying the influences of strain and vorticity in the system. We provide a very detailed account of the behaviour of the liquid crystal in the three dimensional case, when the direction of alignment of the molecules that constitute the liquid crystal is allowed out of the shear plane. We establish that the only out-of-plane steady solution of the system is an anomalous continuum of equilibria, and therefore the Landau-de Gennes model that we are employing is structurally unstable. The time dependent solutions of the liquid crystal fall into one of the following categories: in plane periodic orbits, which are the tumbling and wagging solutions and out-of-plane periodic orbits, the so-called kayaking state. The use of bifurcation theory in the context of nematodynamics allows us to give a complete summary of the nonlinear behaviour of a nematic liquid crystal in a shear flow, for the two and three dimensional cases.