Modeling of non-isothermalvapor membrane separation with thermodynamic models and generalized mass transfer equations

A rigorous unit operation model is developed for vapor membrane separation. The new model is able to describe temperature, pressure, and concentration dependent permeation as wellreal fluid effects in vapor and gas separation with hydrocarbon selective rubbery polymeric membranes. The permeation through the membrane is described by a separate treatment of sorption and diffusion within the membrane. The chemical engineering thermodynamics is used to describe the equilibrium sorption of vapors and gases in rubbery membranes with equation of state models for polymeric systems. Also a new modification of the UNIFAC model is proposed for this purpose. Various thermodynamic models are extensively compared in order to verify the models' ability to predict and correlate experimental vapor-liquid equilibrium data. The penetrant transport through the selective layer of the membrane is described with the generalized Maxwell-Stefan equations, which are able to account for thebulk flux contribution as well as the diffusive coupling effect. A method is described to compute and correlate binary penetrant¿membrane diffusion coefficients from the experimental permeability coefficients at different temperatures and pressures. A fluid flow model for spiral-wound modules is derived from the conservation equation of mass, momentum, and energy. The conservation equations are presented in a discretized form by using the control volume approach. A combination of the permeation model and the fluid flow model yields the desired rigorous model for vapor membrane separation. The model is implemented into an inhouse process simulator and so vapor membrane separation may be evaluated as an integralpart of a process flowsheet.

Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.

A generalized 1D particle transport method for convection diffusion reaction model

This work is devoted to the development of numerical method to deal with convection diffusion dominated problem with reaction term, non - stiff chemical reaction and stiff chemical reaction. The technique is based on the unifying Eulerian - Lagrangian schemes (particle transport method) under the framework of operator splitting method. In the computational domain, the particle set is assigned to solve the convection reaction subproblem along the characteristic curves created by convective velocity. At each time step, convection, diffusion and reaction terms are solved separately by assuming that, each phenomenon occurs separately in a sequential fashion. Moreover, adaptivities and projection techniques are used to add particles in the regions of high gradients (steep fronts) and discontinuities and transfer a solution from particle set onto grid point respectively. The numerical results show that, the particle transport method has improved the solutions of CDR problems. Nevertheless, the method is time consumer when compared with other classical technique e.g., method of lines. Apart from this advantage, the particle transport method can be used to simulate problems that involve movingsteep/smooth fronts such as separation of two or more elements in the system.

Generalized Differential Evolution for Global Multi-Objective Optimization with Constraints

The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

Corrosion behaviour of boiler tube materials during combustion of fuels containing Zn and Pb

Många förbränningsanläggningar som bränner utmanande bränslen såsom restfraktioner och avfall råkar ut för problem med ökad korrosion på överhettare och/eller vattenväggar pga. komponenter i bränslena som är korrosiva. För att minimera problemen i avfallseldade pannor hålls ångparametrarna på en relativt låg nivå, vilket drastiskt minskar energiproduktionen. Beläggningarna i avfallseldade pannor består till största delen av element som är förknippade med högtemperaturkorrosion: Cl, S, alkalimetaller, främst K och Na, och tungmetaller som Pb och Zn, och det finns också indikationer av Br-förekomst. Det låga ångtrycket i avfallseldade pannor påverkar också stålrörens temperatur i pannväggarna i eldstaden. I dagens läge hålls temperaturen normalt vid 300-400 °C. Alkalikloridorsakad (KCl, NaCl) högtemperaturkorrosion har inte rapporterats vara relevant vid såpass låga temperaturer, men närvaro av Zn- och Pb-komponenter i beläggningarna har påvisats förorsaka ökad korrosion redan vid 300-400 °C. Vid förbränning kan Zn och Pb reagera med S och Cl och bilda klorider och sulfater i rökgaserna. Dessa tungmetallföreningar är speciellt problematiska pga. de bildar lågsmältande saltblandningar. Dessa lågsmältande gasformiga eller fasta föreningar följer rökgasen och kan sedan fastna eller kondensera på kallare ytor på pannväggar eller överhettare för att sedan bilda aggressiva beläggningar. Tungmetallrika (Pb, Zn) klorider och sulfater ökar risken för korrosion, och effekten förstärks ytterligare vid närvaro av smälta. Motivet med den här studien var att få en bättre insikt i högtemperaturkorrosion förorsakad av Zn och Pb, samt att undersöka och prediktera beteendet och motståndskraften hos några stålkvaliteter som används i överhettare och pannväggar i tungmetallrika förhållanden och höga materialtemperaturer. Omfattande laboratorie-, småskale- och fullskaletest utfördes. Resultaten kan direkt utnyttjas i praktiska applikationer, t.ex. vid materialval, eller vid utveckling av korrosionsmotverkande verktyg för att hitta initierande faktorer och förstå deras effekt på högtemperaturkorrosion.

The role of potassium in the corrosion of superheater materials in boilers firing biomass

Inhibition of global warming has become one of the major goals for the coming decades. A key strategy is to replace fossil fuels with more sustainable fuels, which has generated growing interest in the use of waste-derived fuels and of biomass fuels. However, from the chemical point of view, biomass is an inhomogeneous fuel, usually with a high concentration of water and considerable amounts of potassium and chlorine, all of which are known to affect the durability of superheater tubes. To slow down or reduce corrosion, power plants using biomass as fuel have been forced to operate at lower steam temperatures as compared to fossil fuel power plants. This reduces power production efficiency: every 10°C rise in the steam temperature results in an approximate increase of 2% in power production efficiency. More efficient ways to prevent corrosion are needed so that power plants using biomass and waste-derived fuels can operate at higher steam temperatures. The aim of this work was to shed more light on the alkali-induced corrosion of superheater steels at elevated temperatures, focusing on potassium chloride, the alkali salt most frequently encountered in biomass combustion, and on potassium carbonate, another potassium salt occasionally found in fly ash. The mechanisms of the reactions between various corrosive compounds and steels were investigated. Based on the results, the potassium-induced accelerated oxidation of chromia protected steels appears to occur in two consecutive stages. In the first, the protective chromium oxide layer is destroyed through a reaction with potassium leading to the formation of intermediates such as potassium chromate (K2CrO4) and depleting the chromium in the protective oxide layer. As the chromium is depleted, chromium from the bulk steel diffuses into the oxide layer to replenish it. In this stage, the ability of the material to withstand corrosion depends on the chromium content (which affects how long it takes the chromium in the oxide layer to be depleted) and on external factors such as temperature (which affects how fast the chromium diffuses into the protective oxide from the bulk steel). For accelerated oxidation to continue, the presence of chloride appears to be essential.