854 resultados para Optimisation solver CPLEX


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Liquid-liquid extraction has long been known as a unit operation that plays an important role in industry. This process is well known for its complexity and sensitivity to operation conditions. This thesis presents an attempt to explore the dynamics and control of this process using a systematic approach and state of the art control system design techniques. The process was studied first experimentally under carefully selected. operation conditions, which resembles the ranges employed practically under stable and efficient conditions. Data were collected at steady state conditions using adequate sampling techniques for the dispersed and continuous phases as well as during the transients of the column with the aid of a computer-based online data logging system and online concentration analysis. A stagewise single stage backflow model was improved to mimic the dynamic operation of the column. The developed model accounts for the variation in hydrodynamics, mass transfer, and physical properties throughout the length of the column. End effects were treated by addition of stages at the column entrances. Two parameters were incorporated in the model namely; mass transfer weight factor to correct for the assumption of no mass transfer in the. settling zones at each stage and the backmixing coefficients to handle the axial dispersion phenomena encountered in the course of column operation. The parameters were estimated by minimizing the differences between the experimental and the model predicted concentration profiles at steady state conditions using non-linear optimisation technique. The estimated values were then correlated as functions of operating parameters and were incorporated in·the model equations. The model equations comprise a stiff differential~algebraic system. This system was solved using the GEAR ODE solver. The calculated concentration profiles were compared to those experimentally measured. A very good agreement of the two profiles was achieved within a percent relative error of ±2.S%. The developed rigorous dynamic model of the extraction column was used to derive linear time-invariant reduced-order models that relate the input variables (agitator speed, solvent feed flowrate and concentration, feed concentration and flowrate) to the output variables (raffinate concentration and extract concentration) using the asymptotic method of system identification. The reduced-order models were shown to be accurate in capturing the dynamic behaviour of the process with a maximum modelling prediction error of I %. The simplicity and accuracy of the derived reduced-order models allow for control system design and analysis of such complicated processes. The extraction column is a typical multivariable process with agitator speed and solvent feed flowrate considered as manipulative variables; raffinate concentration and extract concentration as controlled variables and the feeds concentration and feed flowrate as disturbance variables. The control system design of the extraction process was tackled as multi-loop decentralised SISO (Single Input Single Output) as well as centralised MIMO (Multi-Input Multi-Output) system using both conventional and model-based control techniques such as IMC (Internal Model Control) and MPC (Model Predictive Control). Control performance of each control scheme was. studied in terms of stability, speed of response, sensitivity to modelling errors (robustness), setpoint tracking capabilities and load rejection. For decentralised control, multiple loops were assigned to pair.each manipulated variable with each controlled variable according to the interaction analysis and other pairing criteria such as relative gain array (RGA), singular value analysis (SVD). Loops namely Rotor speed-Raffinate concentration and Solvent flowrate Extract concentration showed weak interaction. Multivariable MPC has shown more effective performance compared to other conventional techniques since it accounts for loops interaction, time delays, and input-output variables constraints.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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In this thesis, standard algorithms are used to carry out the optimisation of cold-formed steel purlins such as zed, channel and sigma sections, which are assumed to be simply supported and subjected to a gravity load. For zed, channel and sigma section, the local buckling, distortional buckling and lateral-torsional buckling are considered respectively herein. Currently, the local buckling is based on the BS 5950-5:1998 and EN 1993-1-3:2006. The distortional buckling is calculated by the direct strength method employing the elastic distortional buckling which is calculated by three available approaches such as Hancock (1995), Schafer and Pekoz (1998), Yu (2005). In the optimisation program, the lateral-torsional buckling based on BS 5950-5:1998, AISI and analytical model of Li (2004) are investigated. For the optimisation program, the programming codes are written for optimisation of channel, zed and sigma beam. The full study has been coded into a computer-based analysis program (MATLAB).

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The aim of the research project was to gain d complete and accurate accounting of the needs and deficiencies of materials selection and design data, with particular attention given to the feasibility of a computerised materials selection system that would include application analysis, property data and screening techniques. The project also investigates and integrates the three major aspects of materials resources, materials selection and materials recycling. Consideration of the materials resource base suggests that, though our discovery potential has increased, geologic availability is the ultimate determinant and several metals may well become scarce at the same time, thus compounding the problem of substitution. With around 2- to 20- million units of engineering materials data, the use of a computer is the only logical answer for scientific selection of materials. The system developed at Aston is used for data storage, mathematical computation and output. The system enables programs to be run in batch and interactive (on-line) mode. The program with modification can also handle such variables as quantity of mineral resources, energy cost of materials and depletion and utilisation rates of strateqic materials. The work also carries out an in-depth study of copper recycling in the U.K. and concludes that, somewhere in the region of 2 million tonnes of copper is missing from the recycling cycle. It also sets out guidelines on product design and conservation policies from the recyclability point of view.

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Service-based systems that are dynamically composed at run time to provide complex, adaptive functionality are currently one of the main development paradigms in software engineering. However, the Quality of Service (QoS) delivered by these systems remains an important concern, and needs to be managed in an equally adaptive and predictable way. To address this need, we introduce a novel, tool-supported framework for the development of adaptive service-based systems called QoSMOS (QoS Management and Optimisation of Service-based systems). QoSMOS can be used to develop service-based systems that achieve their QoS requirements through dynamically adapting to changes in the system state, environment and workload. QoSMOS service-based systems translate high-level QoS requirements specified by their administrators into probabilistic temporal logic formulae, which are then formally and automatically analysed to identify and enforce optimal system configurations. The QoSMOS self-adaptation mechanism can handle reliability- and performance-related QoS requirements, and can be integrated into newly developed solutions or legacy systems. The effectiveness and scalability of the approach are validated using simulations and a set of experiments based on an implementation of an adaptive service-based system for remote medical assistance.

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Despite recent success, rapidly disintegrating lyophilized tablets still face problems of low mechanical strength and higher disintegration times resulting in poor patient compliance. The aim of the current work was to carry out a systematic study to understand the factors controlling mechanical properties of these formulations. The work investigated the influence of two bloom strengths of gelatin: low (60 bloom) and high (225 bloom) at different stock solution concentrations (2, 5, 7.5, and 10 %w/w). This was followed by investigation of addition of five saccharides (xylitol, glucose, trehalose, maltotriose and mannitol) at varied concentration range (10-80 %w/w) to decipher their influence on disintegration time, mechanical and thermal properties of the formulation. The results indicated that the disintegration time of the tablets dramatically decreased by decreasing the concentration and bloom strength of gelatin in the stock solution. However the mechanical properties of the tablets were mainly influenced by the concentration of gelatin rather than the bloom strength. The addition of saccharides resulted in enhancement of tablet properties and was concentration dependent. All the saccharides improved the fractubility of the tablets significantly at high concentration (equal or higher than 40% w/w). However, only high concentration (equal or higher than 40% w/w) of trehalose, maltotriose and mannitol significantly enhanced the hardness. Additionally, mannitol crytallised during freeze drying and consequently produced elegant tablets, whilst the other saccarides exhibited lyoprotectant activity as they were able to retain amorphous status. Based on the above findings, an optimized formulation was also successfully developed and characterized to deliver 100 microg dose of Clonidine HCl.

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The primary objective of this work is to relate the biomass fuel quality to fast pyrolysis-oil quality in order to identify key biomass traits which affect pyrolysis-oil stability. During storage the pyrolysis-oil becomes more viscous due to chemical and physical changes, as reactions and volatile losses occur due to aging. The reason for oil instability begins within the pyrolysis reactor during pyrolysis in which the biomass is rapidly heated in the absence of oxygen, producing free radical volatiles which are then quickly condensed to form the oil. The products formed do not reach thermodynamic equilibrium and in tum the products react with each other to try to achieve product stability. The first aim of this research was to develop and validate a rapid screening method for determining biomass lignin content in comparison to traditional, time consuming and hence costly wet chemical methods such as Klason. Lolium and Festuca grasses were selected to validate the screening method, as these grass genotypes exhibit a low range of Klason /Acid Digestible Fibre lignin contents. The screening methodology was based on the relationship between the lignin derived products from pyrolysis and the lignin content as determined by wet chemistry. The second aim of the research was to determine whether metals have an affect on fast pyrolysis products, and if any clear relationships can be deduced to aid research in feedstock selection for fast pyrolysis processing. It was found that alkali metals, particularly Na and K influence the rate and yield of degradation as well the char content. Pre-washing biomass with water can remove 70% of the total metals, and improve the pyrolysis product characteristics by increasing the organic yield, the temperature in which maximum liquid yield occurs and the proportion of higher molecular weight compounds within the pyrolysis-oil. The third aim identified these feedstock traits and relates them to the pyrolysis-oil quality and stability. It was found that the mineral matter was a key determinant on pyrolysis-oil yield compared to the proportion of lignin. However the higher molecular weight compounds present in the pyrolysis-oil are due to the lignin, and can cause instability within the pyrolysis-oil. The final aim was to investigate if energy crops can be enhanced by agronomical practices to produce a biomass quality which is attractive to the biomass conversion community, as well as giving a good yield to the farmers. It was found that the nitrogen/potassium chloride fertiliser treatments enhances Miscanthus qualities, by producing low ash, high volatiles yields with acceptable yields for farmers. The progress of senescence was measured in terms of biomass characteristics and fast pyrolysis product characteristics. The results obtained from this research are in strong agreement with published literature, and provides new information on quality traits for biomass which affects pyrolysis and pyrolysis-oils.

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Analysis of the use of ICT in the aerospace industry has prompted the detailed investigation of an inventory-planning problem. There is a special class of inventory, consisting of expensive repairable spares for use in support of aircraft operations. These items, called rotables, are not well served by conventional theory and systems for inventory management. The context of the problem, the aircraft maintenance industry sector, is described in order to convey some of its special characteristics in the context of operations management. A literature review is carried out to seek existing theory that can be applied to rotable inventory and to identify a potential gap into which newly developed theory could contribute. Current techniques for rotable planning are identified in industry and the literature: these methods are modelled and tested using inventory and operational data obtained in the field. In the expectation that current practice leaves much scope for improvement, several new models are proposed. These are developed and tested on the field data for comparison with current practice. The new models are revised following testing to give improved versions. The best model developed and tested here comprises a linear programming optimisation, which finds an optimal level of inventory for multiple test cases, reflecting changing operating conditions. The new model offers an inventory plan that is up to 40% less expensive than that determined by current practice, while maintaining required performance.

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This thesis presents research within empirical financial economics with focus on liquidity and portfolio optimisation in the stock market. The discussion on liquidity is focused on measurement issues, including TAQ data processing and measurement of systematic liquidity factors (FSO). Furthermore, a framework for treatment of the two topics in combination is provided. The liquidity part of the thesis gives a conceptual background to liquidity and discusses several different approaches to liquidity measurement. It contributes to liquidity measurement by providing detailed guidelines on the data processing needed for applying TAQ data to liquidity research. The main focus, however, is the derivation of systematic liquidity factors. The principal component approach to systematic liquidity measurement is refined by the introduction of moving and expanding estimation windows, allowing for time-varying liquidity co-variances between stocks. Under several liability specifications, this improves the ability to explain stock liquidity and returns, as compared to static window PCA and market average approximations of systematic liquidity. The highest ability to explain stock returns is obtained when using inventory cost as a liquidity measure and a moving window PCA as the systematic liquidity derivation technique. Systematic factors of this setting also have a strong ability in explaining a cross-sectional liquidity variation. Portfolio optimisation in the FSO framework is tested in two empirical studies. These contribute to the assessment of FSO by expanding the applicability to stock indexes and individual stocks, by considering a wide selection of utility function specifications, and by showing explicitly how the full-scale optimum can be identified using either grid search or the heuristic search algorithm of differential evolution. The studies show that relative to mean-variance portfolios, FSO performs well in these settings and that the computational expense can be mitigated dramatically by application of differential evolution.

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Inference and optimisation of real-value edge variables in sparse graphs are studied using the tree based Bethe approximation optimisation algorithms. Equilibrium states of general energy functions involving a large set of real edge-variables that interact at the network nodes are obtained for networks in various cases. These include different cost functions, connectivity values, constraints on the edge bandwidth and the case of multiclass optimisation.