890 resultados para combinatorial optimisation


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A massive change is currently taking place in the manner in which power networks are operated. Traditionally, power networks consisted of large power stations which were controlled from centralised locations. The trend in modern power networks is for generated power to be produced by a diverse array of energy sources which are spread over a large geographical area. As a result, controlling these systems from a centralised controller is impractical. Thus, future power networks will be controlled by a large number of intelligent distributed controllers which must work together to coordinate their actions. The term Smart Grid is the umbrella term used to denote this combination of power systems, artificial intelligence, and communications engineering. This thesis focuses on the application of optimal control techniques to Smart Grids with a focus in particular on iterative distributed MPC. A novel convergence and stability proof for iterative distributed MPC based on the Alternating Direction Method of Multipliers is derived. Distributed and centralised MPC, and an optimised PID controllers' performance are then compared when applied to a highly interconnected, nonlinear, MIMO testbed based on a part of the Nordic power grid. Finally, a novel tuning algorithm is proposed for iterative distributed MPC which simultaneously optimises both the closed loop performance and the communication overhead associated with the desired control.

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This thesis describes the optimisation of chemoenzymatic methods in asymmetric synthesis. Modern synthetic organic chemistry has experienced an enormous growth in biocatalytic methodologies; enzymatic transformations and whole cell bioconversions have become generally accepted synthetic tools for asymmetric synthesis. Biocatalysts are exceptional catalysts, combining broad substrate scope with high regio-, enantio- and chemoselectivities enabling the resolution of organic substrates with superb efficiency and selectivity. In this study three biocatalytic applications in enantioselective synthesis were explored and perhaps the most significant outcome of this work is the excellent enantioselectivity achieved through optimisation of reaction conditions improving the synthetic utility of the biotransformations. In the first chapter a summary of literature discussing the stereochemical control of baker’s yeast (Saccharomyces Cerevisae) mediated reduction of ketones by the introduction of sulfur moieties is presented, and sets the work of Chapter 2 in context. The focus of the second chapter was the synthesis and biocatalytic resolution of (±)-trans-2-benzenesulfonyl-3-n-butylcyclopentanone. For the first time the practical limitations of this resolution have been addressed providing synthetically useful quantities of enantiopure synthons for application in the total synthesis of both enantiomers of 4-methyloctanoic acid, the aggregation pheromone of the rhinoceros beetles of the genus Oryctes. The unique aspect of this enantioselective synthesis was the overall regio- and enantioselective introduction of the methyl group to the octanoic acid chain. This work is part of an ongoing research programme in our group focussed on baker’s yeast mediated kinetic resolution of 2-keto sulfones. The third chapter describes hydrolase-catalysed kinetic resolutions leading to a series of 3-aryl alkanoic acids. Hydrolysis of the ethyl esters with a series of hydrolases was undertaken to identify biocatalysts that yield the corresponding acids in highly enantioenriched form. Contrary to literature reports where a complete disappearance of efficiency and, accordingly enantioselection, was described upon kinetic resolution of sterically demanding 3-arylalkanoic acids, the highest reported enantiopurities of these acids was achieved (up to >98% ee) in this study through optimisation of reaction conditions. Steric and electronic effects on the efficiency and enantioselectivity of the biocatalytic transformation were also explored. Furthermore, a novel approach to determine the absolute stereochemistry of the enantiopure 3-aryl alkanoic acids was investigated through combination of co-crystallisation and X-ray diffraction linked with chiral HPLC analysis. The fourth chapter was focused on the development of a biocatalytic protocol for the asymmetric Henry reaction. Efficient kinetic resolution in hydrolase-mediated transesterification of cis- and trans- β-nitrocyclohexanol derivatives was achieved. Combination of a base-catalysed intramolecular Henry reaction coupled with the hydrolase-mediated kinetic resolution with the view to selective acetylation of a single stereoisomer was investigated. While dynamic kinetic resolution in the intramolecular Henry was not achieved, significant progress in each of the individual elements was made and significantly the feasibility of this process has been demonstrated. The final chapter contains the full experimental details, including spectroscopic and analytical data of all compounds synthesised in this project, while details of chiral HPLC analysis are included in the appendix. The data for the crystal structures are contained in the attached CD.

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In the European Union under the Common Agricultural Policy (CAP) milk production was restricted by milk quotas since 1984. However, due to recent changes in the Common Agricultural Policy (CAP), milk quotas will be abolished by 2015. Therefore, the European dairy sector will soon face an opportunity, for the first time in a generation, to expand. Numerous studies have shown that milk production in Ireland will increase significantly post quotas (Laepple and Hennessy (2010), Donnellan and Hennessy (2007) and Lips and Reider (2005)). The research in this thesis explored milk transport and dairy product processing in the Irish dairy processing sector in the context of milk quota removal and expansion by 2020. In this study a national milk transport model was developed for the Irish dairy industry, the model was used to examine different efficiency factors in milk transport and to estimate milk transport costs post milk quota abolition. Secondly, the impact of different milk supply profiles on milk transport costs was investigated using the milk transport model. Current processing capacity in Ireland was compared against future supply, it was concluded that additional milk processing capacity would not be sufficient to process the additional milk. Thirdly, the milk transport model was used to identify the least cost locations (based on transport costs) to process the additional milk supply in 2020. Finally, an optimisation model was developed to identify the optimum configuration for the Irish dairy processing sector in 2020 taking cognisance of increasing transport costs and decreasing processing costs.

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Cancer represents a leading of cause of death in the developed world, inflicting tremendous suffering and plundering billions from health budgets. The traditional treatment approaches of surgery, radiotherapy and chemotherapy have achieved little in terms of cure for this deadly disease. Instead, life is prolonged for many, with dubious quality of life, only for disease to reappear with the inevitable fatal outcome. “Blue sky” thinking is required to tackle this disease and improve outcomes. The realisation and acceptance of the intrinsic role of the immune system in cancer pathogenesis, pathophysiology and treatment represented such a “blue sky” thought. Moreover, the embracement of immunotherapy, the concept of targeting immune cells rather than the tumour cells themselves, represents a paradigm shift in the approach to cancer therapy. The harnessing of immunotherapy demands radical and innovative therapeutic endeavours – endeavours such as gene and cell therapies and RNA interference, which two decades ago existed as mere concepts. This thesis straddles the frontiers of fundamental tumour immunobiology and novel therapeutic discovery, design and delivery. The work undertaken focused on two distinct immune cell populations known to undermine the immune response to cancer – suppressive T cells and macrophages. Novel RNAi mediators were designed, validated and incorporated into clinically relevant gene therapy vectors – involving a traditional lentiviral vector approach, and a novel bacterial vector strategy. Chapter 2 deals with the design of novel RNAi mediators against FOXP3 – a crucial regulator of the immunosuppressive regulatory T cell population. Two mediators were tested and validated. The superior mediator was taken forward as part of work in chapter 3. Chapter 3 deals with transposing the RNA sequence from chapter 2 into a DNA-based construct and subsequent incorporation into a lentiviral-based vector system. The lentiviral vector was shown to mediate gene delivery in vitro and functional RNAi was achieved against FOXP3. Proof of gene delivery was further confirmed in vivo in tumour-bearing animals. Chapter 4 focuses on a different immune cell population – tumour-associated macrophages. Non-invasive bacteria were explored as a specific means of delivering gene therapy to this phagocytic cell type. Proof of delivery was shown in vitro and in vivo. Moreover, in vivo delivery of a gene by this method achieved the desired immune response in terms of cytokine profile. Overall, the data presented here advance exploration within the field of cancer immunotherapy, introduce novel delivery and therapeutic strategies, and demonstrate pre-clinically the potential for such novel anti-cancer therapies.

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This thesis investigates the optimisation of Coarse-Fine (CF) spectrum sensing architectures under a distribution of SNRs for Dynamic Spectrum Access (DSA). Three different detector architectures are investigated: the Coarse-Sorting Fine Detector (CSFD), the Coarse-Deciding Fine Detector (CDFD) and the Hybrid Coarse-Fine Detector (HCFD). To date, the majority of the work on coarse-fine spectrum sensing for cognitive radio has focused on a single value for the SNR. This approach overlooks the key advantage that CF sensing has to offer, namely that high powered signals can be easily detected without extra signal processing. By considering a range of SNR values, the detector can be optimised more effectively and greater performance gains realised. This work considers the optimisation of CF spectrum sensing schemes where the security and performance are treated separately. Instead of optimising system performance at a single, constant, low SNR value, the system instead is optimised for the average operating conditions. The security is still provided such that at the low SNR values the safety specifications are met. By decoupling the security and performance, the system’s average performance increases whilst maintaining the protection of licensed users from harmful interference. The different architectures considered in this thesis are investigated in theory, simulation and physical implementation to provide a complete overview of the performance of each system. This thesis provides a method for estimating SNR distributions which is quick, accurate and relatively low cost. The CSFD is modelled and the characteristic equations are found for the CDFD scheme. The HCFD is introduced and optimisation schemes for all three architectures are proposed. Finally, using the Implementing Radio In Software (IRIS) test-bed to confirm simulation results, CF spectrum sensing is shown to be significantly quicker than naive methods, whilst still meeting the required interference probability rates and not requiring substantial receiver complexity increases.

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Reflective modulators based on the combination of an electroabsorption modulator (EAM) and semiconductor optical amplifier (SOA) are attractive devices for applications in long reach carrier distributed passive optical networks (PONs) due to the gain provided by the SOA and the high speed and low chirp modulation of the EAM. Integrated R-EAM-SOAs have experimentally shown two unexpected and unintuitive characteristics which are not observed in a single pass transmission SOA: the clamping of the output power of the device around a maximum value and low patterning distortion despite the SOA being in a regime of gain saturation. In this thesis a detailed analysis is carried out using both experimental measurements and modelling in order to understand these phenomena. For the first time it is shown that both the internal loss between SOA and R-EAM and the SOA gain play an integral role in the behaviour of gain saturated R-EAM-SOAs. Internal loss and SOA gain are also optimised for use in a carrier distributed PONs in order to access both the positive effect of output power clamping, and hence upstream dynamic range reduction, combined with low patterning operation of the SOA Reflective concepts are also gaining interest for metro transport networks and short reach, high bit rate, inter-datacentre links. Moving the optical carrier generation away from the transmitter also has potential advantages for these applications as it avoids the need for cooled photonics being placed directly on hot router line-cards. A detailed analysis is carried out in this thesis on a novel colourless reflective duobinary modulator, which would enable wavelength flexibility in a power-efficient reflective metro node.

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The combinatorial model of nuclear level densities has now reached a level of accuracy comparable to that of the best global analytical expressions without suffering from the limits imposed by the statistical hypothesis on which the latter expressions rely. In particular, it provides, naturally, non-Gaussian spin distribution as well as non-equipartition of parities which are known to have an impact on cross section predictions at low energies [1, 2, 3]. Our previous global models developed in Refs. [1, 2] suffered from deficiencies, in particular in the way the collective effects - both vibrational and rotational - were treated. We have recently improved this treatment using simultaneously the single-particle levels and collective properties predicted by a newly derived Gogny interaction [4], therefore enabling a microscopic description of energy-dependent shell, pairing and deformation effects. In addition for deformed nuclei, the transition to sphericity is coherently taken into account on the basis of a temperature-dependent Hartree-Fock calculation which provides at each temperature the structure properties needed to build the level densities. This new method is described and shown to give promising results with respect to available experimental data.

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The interactions between water curtain protective barriers and impinging cold gas clouds released during industrial accidents are simulated by a 2D finite difference code using a PSI-cell of the heat, mass and momentum transfer processes between the phases. A consistent derivation of the continuous phase source terms is presented. The results of early simulations of an existing 1:10 experimental model of a water curtain impacted by a cold gas cloud are presented for two typical curtain configurations.

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The paper describes the design of an efficient and robust genetic algorithm for the nuclear fuel loading problem (i.e., refuellings: the in-core fuel management problem) - a complex combinatorial, multimodal optimisation., Evolutionary computation as performed by FUELGEN replaces heuristic search of the kind performed by the FUELCON expert system (CAI 12/4), to solve the same problem. In contrast to the traditional genetic algorithm which makes strong requirements on the representation used and its parameter setting in order to be efficient, the results of recent research results on new, robust genetic algorithms show that representations unsuitable for the traditional genetic algorithm can still be used to good effect with little parameter adjustment. The representation presented here is a simple symbolic one with no linkage attributes, making the genetic algorithm particularly easy to apply to fuel loading problems with differing core structures and assembly inventories. A nonlinear fitness function has been constructed to direct the search efficiently in the presence of the many local optima that result from the constraint on solutions.

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Three parallel optimisation algorithms, for use in the context of multilevel graph partitioning of unstructured meshes, are described. The first, interface optimisation, reduces the computation to a set of independent optimisation problems in interface regions. The next, alternating optimisation, is a restriction of this technique in which mesh entities are only allowed to migrate between subdomains in one direction. The third treats the gain as a potential field and uses the concept of relative gain for selecting appropriate vertices to migrate. The results are compared and seen to produce very high global quality partitions, very rapidly. The results are also compared with another partitioning tool and shown to be of higher quality although taking longer to compute.

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FEA and CFD analysis is becoming ever more complex with an emerging demand for simulation software technologies that can address ranges of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and length scales. Computation modelling of such problems requires software technologies that enable the representation of these complex suites of 'physical' interactions. This functionality requires the structuring of simulation modules for specific physical phemonmena so that the coupling can be effectiely represented. These 'multi-physics' and 'multi-scale' computations are very compute intensive and so the simulation software must operate effectively in parallel if it is to be used in this context. Of course the objective of 'multi-physics' and 'multi-scale' simulation is the optimal design of engineered systems so optimistation is an important feature of such classes of simulation. In this presentation, a multi-disciplinary approach to simulation based optimisation is described with some key examples of application to challenging engineering problems.

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This paper details and demonstrates integrated optimisation-reliability modelling for predicting the performance of solder joints in electronic packaging. This integrated modelling approach is used to identify efficiently and quickly the most suitable design parameters for solder joint performance during thermal cycling and is demonstrated on flip-chip components using “no-flow” underfills. To implement “optimisation in reliability” approach, the finite element simulation tool – PHYSICA, is coupled with optimisation and statistical tools. This resulting framework is capable of performing design optimisation procedures in an entirely automated and systematic manner.

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The aim of integrating computational mechanics (FEA and CFD) and optimization tools is to speed up dramatically the design process in different application areas concerning reliability in electronic packaging. Design engineers in the electronics manufacturing sector may use these tools to predict key design parameters and configurations (i.e. material properties, product dimensions, design at PCB level. etc) that will guarantee the required product performance. In this paper a modeling strategy coupling computational mechanics techniques with numerical optimization is presented and demonstrated with two problems. The integrated modeling framework is obtained by coupling the multi-physics analysis tool PHYSICA - with the numerical optimization package - Visua/DOC into a fuJly automated design tool for applications in electronic packaging. Thermo-mechanical simulations of solder creep deformations are presented to predict flip-chip reliability and life-time under thermal cycling. Also a thermal management design based on multi-physics analysis with coupled thermal-flow-stress modeling is discussed. The Response Surface Modeling Approach in conjunction with Design of Experiments statistical tools is demonstrated and used subsequently by the numerical optimization techniques as a part of this modeling framework. Predictions for reliable electronic assemblies are achieved in an efficient and systematic manner.