Model based study of a calcium oxide looping process for post-combustion carbon dioxide capture

Calcium oxide looping is a carbon dioxide sequestration technique that utilizes the partially reversible reaction between limestone and carbon dioxide in two interconnected fluidised beds, carbonator and calciner. Flue gases from a combustor are fed into the carbonator where calcium oxide reacts with carbon dioxide within the gases at a temperature of 650 ºC. Calcium oxide is transformed into calcium carbonate which is circulated into the regenerative calciner, where calcium carbonate is returned into calcium oxide and a stream of pure carbon dioxide at a higher temperature of 950 ºC. Calcium oxide looping has proved to have a low impact on the overall process efficiency and would be easily retrofitted into existing power plants. This master’s thesis is done in participation to an EU funded project CaOling as a part of the Lappeenranta University of Technology deliverable, reactor modelling and scale-up tools. Thesis concentrates in creating the first model frame and finding the physically relevant phenomena governing the process.

Effect of hydrodynamics on modelling, monitoring and control of crystallization

Crystallization is a purification method used to obtain crystalline product of a certain crystal size. It is one of the oldest industrial unit processes and commonly used in modern industry due to its good purification capability from rather impure solutions with reasonably low energy consumption. However, the process is extremely challenging to model and control because it involves inhomogeneous mixing and many simultaneous phenomena such as nucleation, crystal growth and agglomeration. All these phenomena are dependent on supersaturation, i.e. the difference between actual liquid phase concentration and solubility. Homogeneous mass and heat transfer in the crystallizer would greatly simplify modelling and control of crystallization processes, such conditions are, however, not the reality, especially in industrial scale processes. Consequently, the hydrodynamics of crystallizers, i.e. the combination of mixing, feed and product removal flows, and recycling of the suspension, needs to be thoroughly investigated. Understanding of hydrodynamics is important in crystallization, especially inlargerscale equipment where uniform flow conditions are difficult to attain. It is also important to understand different size scales of mixing; micro-, meso- and macromixing. Fast processes, like nucleation and chemical reactions, are typically highly dependent on micro- and mesomixing but macromixing, which equalizes the concentrations of all the species within the entire crystallizer, cannot be disregarded. This study investigates the influence of hydrodynamics on crystallization processes. Modelling of crystallizers with the mixed suspension mixed product removal (MSMPR) theory (ideal mixing), computational fluid dynamics (CFD), and a compartmental multiblock model is compared. The importance of proper verification of CFD and multiblock models is demonstrated. In addition, the influence of different hydrodynamic conditions on reactive crystallization process control is studied. Finally, the effect of extreme local supersaturation is studied using power ultrasound to initiate nucleation. The present work shows that mixing and chemical feeding conditions clearly affect induction time and cluster formation, nucleation, growth kinetics, and agglomeration. Consequently, the properties of crystalline end products, e.g. crystal size and crystal habit, can be influenced by management of mixing and feeding conditions. Impurities may have varying impacts on crystallization processes. As an example, manganese ions were shown to replace magnesium ions in the crystal lattice of magnesium sulphate heptahydrate, increasing the crystal growth rate significantly, whereas sodium ions showed no interaction at all. Modelling of continuous crystallization based on MSMPR theory showed that the model is feasible in a small laboratoryscale crystallizer, whereas in larger pilot- and industrial-scale crystallizers hydrodynamic effects should be taken into account. For that reason, CFD and multiblock modelling are shown to be effective tools for modelling crystallization with inhomogeneous mixing. The present work shows also that selection of the measurement point, or points in the case of multiprobe systems, is crucial when process analytical technology (PAT) is used to control larger scale crystallization. The thesis concludes by describing how control of local supersaturation by highly localized ultrasound was successfully applied to induce nucleation and to control polymorphism in reactive crystallization of L-glutamic acid.

A study of combustion phenomena in circulating fluidized beds by developing and applying experimental and modelling methods for laboratory-scale reactors

The results shown in this thesis are based on selected publications of the 2000s decade. The work was carried out in several national and EC funded public research projects and in close cooperation with industrial partners. The main objective of the thesis was to study and quantify the most important phenomena of circulating fluidized bed combustors by developing and applying proper experimental and modelling methods using laboratory scale equipments. An understanding of the phenomena plays an essential role in the development of combustion and emission performance, and the availability and controls of CFB boilers. Experimental procedures to study fuel combustion behaviour under CFB conditions are presented in the thesis. Steady state and dynamic measurements under well controlled conditions were carried out to produce the data needed for the development of high efficiency, utility scale CFB technology. The importance of combustion control and furnace dynamics is emphasized when CFB boilers are scaled up with a once through steam cycle. Qualitative information on fuel combustion characteristics was obtained directly by comparing flue gas oxygen responses during the impulse change experiments with fuel feed. A one-dimensional, time dependent model was developed to analyse the measurement data Emission formation was studied combined with fuel combustion behaviour. Correlations were developed for NO, N2O, CO and char loading, as a function of temperature and oxygen concentration in the bed area. An online method to characterize char loading under CFB conditions was developed and validated with the pilot scale CFB tests. Finally, a new method to control air and fuel feeds in CFB combustion was introduced. The method is based on models and an analysis of the fluctuation of the flue gas oxygen concentration. The effect of high oxygen concentrations on fuel combustion behaviour was also studied to evaluate the potential of CFB boilers to apply oxygenfiring technology to CCS. In future studies, it will be necessary to go through the whole scale up chain from laboratory phenomena devices through pilot scale test rigs to large scale, commercial boilers in order to validate the applicability and scalability of the, results. This thesis shows the chain between the laboratory scale phenomena test rig (bench scale) and the CFB process test rig (pilot). CFB technology has been scaled up successfully from an industrial scale to a utility scale during the last decade. The work shown in the thesis, for its part, has supported the development by producing new detailed information on combustion under CFB conditions.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

Electric-drive-based control and electric energy regeneration in a hydraulic system

Over the recent years, development in mobile working machines has concentrated on reducing emissions owing to the tightening rules and needs to improve energy utilization and reduce power losses. This study focuses on energy utilization and regeneration in an electro-hydraulic forklift, which is a lifting equipment application. The study starts from the modelling and simulation of a hydraulic forklift. The energy regeneration from the potential energy of the load was studied. Also a flow-based electric motor speed control was suggested in this thesis instead of the throttle control method or the variable displacement pump control. Topics related to further development in the future are discussed. Finally, a summary and conclusions are presented.

Orthogonal function method in modelling paper web quality variation

This work is devoted to the analysis of signal variation of the Cross-Direction and Machine-Direction measurements from paper web. The data that we possess comes from the real paper machine. Goal of the work is to reconstruct the basis weight structure of the paper and to predict its behaviour to the future. The resulting synthetic data is needed for simulation of paper web. The main idea that we used for describing the basis weight variation in the Cross-Direction is Empirical Orthogonal Functions (EOF) algorithm, which is closely related to Principal Component Analysis (PCA) method. Signal forecasting in time is based on Time-Series analysis. Two principal mathematical procedures that we used in the work are Autoregressive-Moving Average (ARMA) modelling and Ornstein–Uhlenbeck (OU) process.

Modelling of combustion and sorbent reactions in three-dimensional flow environment of a circulating fluidized bed furnace

This thesis presents a three-dimensional, semi-empirical, steady state model for simulating the combustion, gasification, and formation of emissions in circulating fluidized bed (CFB) processes. In a large-scale CFB furnace, the local feeding of fuel, air, and other input materials, as well as the limited mixing rate of different reactants produce inhomogeneous process conditions. To simulate the real conditions, the furnace should be modelled three-dimensionally or the three-dimensional effects should be taken into account. The only available methods for simulating the large CFB furnaces three-dimensionally are semi-empirical models, which apply a relatively coarse calculation mesh and a combination of fundamental conservation equations, theoretical models and empirical correlations. The number of such models is extremely small. The main objective of this work was to achieve a model which can be applied to calculating industrial scale CFB boilers and which can simulate all the essential sub-phenomena: fluid dynamics, reactions, the attrition of particles, and heat transfer. The core of the work was to develop the model frame and the required sub-models for determining the combustion and sorbent reactions. The objective was reached, and the developed model was successfully used for studying various industrial scale CFB boilers combusting different types of fuel. The model for sorbent reactions, which includes the main reactions for calcitic limestones, was applied for studying the new possible phenomena occurring in the oxygen-fired combustion. The presented combustion and sorbent models and principles can be utilized in other model approaches as well, including other empirical and semi-empirical model approaches, and CFD based simulations. The main achievement is the overall model frame which can be utilized for the further development and testing of new sub-models and theories, and for concentrating the knowledge gathered from the experimental work carried out at bench scale, pilot scale and industrial scale apparatus, and from the computational work performed by other modelling methods.

Feature selection using Fuzzy Entropy measures with Yu's Similarity measure

In this study, feature selection in classification based problems is highlighted. The role of feature selection methods is to select important features by discarding redundant and irrelevant features in the data set, we investigated this case by using fuzzy entropy measures. We developed fuzzy entropy based feature selection method using Yu's similarity and test this using similarity classifier. As the similarity classifier we used Yu's similarity, we tested our similarity on the real world data set which is dermatological data set. By performing feature selection based on fuzzy entropy measures before classification on our data set the empirical results were very promising, the highest classification accuracy of 98.83% was achieved when testing our similarity measure to the data set. The achieved results were then compared with some other results previously obtained using different similarity classifiers, the obtained results show better accuracy than the one achieved before. The used methods helped to reduce the dimensionality of the used data set, to speed up the computation time of a learning algorithm and therefore have simplified the classification task

Loss Modelling of Three-Level Inverters controlled with Space Vector Modulation Technique

The objective of this master’s thesis is to investigate the loss behavior of three-level ANPC inverter and compare it with conventional NPC inverter. The both inverters are controlled with mature space vector modulation strategy. In order to provide the comparison both accurate and detailed enough NPC and ANPC simulation models should be obtained. The similar control model of SVM is utilized for both NPC and ANPC inverter models. The principles of control algorithms, the structure and description of models are clarified. The power loss calculation model is based on practical calculation approaches with certain assumptions. The comparison between NPC and ANPC topologies is presented based on results obtained for each semiconductor device, their switching and conduction losses and efficiency of the inverters. Alternative switching states of ANPC topology allow distributing losses among the switches more evenly, than in NPC inverter. Obviously, the losses of a switching device depend on its position in the topology. Losses distribution among the components in ANPC topology allows reducing the stress on certain switches, thus losses are equally distributed among the semiconductors, however the efficiency of the inverters is the same. As a new contribution to earlier studies, the obtained models of SVM control, NPC and ANPC inverters have been built. Thus, this thesis can be used in further more complicated modelling of full-power converters for modern multi-megawatt wind energy conversion systems.

Simulation methods in the modelling of bioaffinity assays

Computational model-based simulation methods were developed for the modelling of bioaffinity assays. Bioaffinity-based methods are widely used to quantify a biological substance in biological research, development and in routine clinical in vitro diagnostics. Bioaffinity assays are based on the high affinity and structural specificity between the binding biomolecules. The simulation methods developed are based on the mechanistic assay model, which relies on the chemical reaction kinetics and describes the forming of a bound component as a function of time from the initial binding interaction. The simulation methods were focused on studying the behaviour and the reliability of bioaffinity assay and the possibilities the modelling methods of binding reaction kinetics provide, such as predicting assay results even before the binding reaction has reached equilibrium. For example, a rapid quantitative result from a clinical bioaffinity assay sample can be very significant, e.g. even the smallest elevation of a heart muscle marker reveals a cardiac injury. The simulation methods were used to identify critical error factors in rapid bioaffinity assays. A new kinetic calibration method was developed to calibrate a measurement system by kinetic measurement data utilizing only one standard concentration. A nodebased method was developed to model multi-component binding reactions, which have been a challenge to traditional numerical methods. The node-method was also used to model protein adsorption as an example of nonspecific binding of biomolecules. These methods have been compared with the experimental data from practice and can be utilized in in vitro diagnostics, drug discovery and in medical imaging.

Element speciation and behaviour in metal-rich Boreal river and estuarine systems using ultrafiltration and chemical modelling

The bioavailability of metals and their potential for environmental pollution depends not simply on total concentrations, but is to a great extent determined by their chemical form. Consequently, knowledge of aqueous metal species is essential in investigating potential metal toxicity and mobility. The overall aim of this thesis is, thus, to determine the species of major and trace elements and the size distribution among the different forms (e.g. ions, molecules and mineral particles) in selected metal-enriched Boreal river and estuarine systems by utilising filtration techniques and geochemical modelling. On the basis of the spatial physicochemical patterns found, the fractionation and complexation processes of elements (mainly related to input of humic matter and pH-change) were examined. Dissolved (<1 kDa), colloidal (1 kDa-0.45 μm) and particulate (>0.45 μm) size fractions of sulfate, organic carbon (OC) and 44 metals/metalloids were investigated in the extremely acidic Vörå River system and its estuary in W Finland, and in four river systems in SW Finland (Sirppujoki, Laajoki, Mynäjoki and Paimionjoki), largely affected by soil erosion and acid sulfate (AS) soils. In addition, geochemical modelling was used to predict the formation of free ions and complexes in these investigated waters. One of the most important findings of this study is that the very large amounts of metals known to be released from AS soils (including Al, Ca, Cd, Co, Cu, Mg, Mn, Na, Ni, Si, U and the lanthanoids) occur and can prevail mainly in toxic forms throughout acidic river systems; as free ions and/or sulfate-complexes. This has serious effects on the biota and especially dissolved Al is expected to have acute effects on fish and other organisms, but also other potentially toxic dissolved elements (e.g. Cd, Cu, Mn and Ni) can have fatal effects on the biota in these environments. In upstream areas that are generally relatively forested (higher pH and contents of OC) fewer bioavailable elements (including Al, Cu, Ni and U) may be found due to complexation with the more abundantly occurring colloidal OC. In the rivers in SW Finland total metal concentrations were relatively high, but most of the elements occurred largely in a colloidal or particulate form and even elements expected to be very soluble (Ca, K, Mg, Na and Sr) occurred to a large extent in colloidal form. According to geochemical modelling, these patterns may only to a limited extent be explained by in-stream metal complexation/adsorption. Instead there were strong indications that the high metal concentrations and dominant solid fractions were largely caused by erosion of metal bearing phyllosilicates. A strong influence of AS soils, known to exist in the catchment, could be clearly distinguished in the Sirppujoki River as it had very high concentrations of a metal sequence typical of AS soils in a dissolved form (Ba, Br, Ca, Cd, Co, K, Mg, Mn, Na, Ni, Rb and Sr). In the Paimionjoki River, metal concentrations (including Ba, Cs, Fe, Hf, Pb, Rb, Si, Th, Ti, Tl and V; not typical of AS soils in the area) were high, but it was found that the main cause of this was erosion of metal bearing phyllosilicates and thus these metals occurred dominantly in less toxic colloidal and particulate fractions. In the two nearby rivers (Laajoki and Mynäjoki) there was influence of AS soils, but it was largely masked by eroded phyllosilicates. Consequently, rivers draining clay plains sensitive to erosion, like those in SW Finland, have generally high background metal concentrations due to erosion. Thus, relying on only semi-dissolved (<0.45 μm) concentrations obtained in routine monitoring, or geochemical modelling based on such data, can lead to a great overestimation of the water toxicity in this environment. The potentially toxic elements that are of concern in AS soil areas will ultimately be precipitated in the recipient estuary or sea, where the acidic metalrich river water will gradually be diluted/neutralised with brackish seawater. Along such a rising pH gradient Al, Cu and U will precipitate first together with organic matter closest to the river mouth. Manganese is relatively persistent in solution and, thus, precipitates further down the estuary as Mn oxides together with elements such as Ba, Cd, Co, Cu and Ni. Iron oxides, on the contrary, are not important scavengers of metals in the estuary, they are predicted to be associated only with As and PO4.

Scaling up stepwise feature introduction to construction of large software systems

Developing software is a difficult and error-prone activity. Furthermore, the complexity of modern computer applications is significant. Hence,an organised approach to software construction is crucial. Stepwise Feature Introduction – created by R.-J. Back – is a development paradigm, in which software is constructed by adding functionality in small increments. The resulting code has an organised, layered structure and can be easily reused. Moreover, the interaction with the users of the software and the correctness concerns are essential elements of the development process, contributing to high quality and functionality of the final product. The paradigm of Stepwise Feature Introduction has been successfully applied in an academic environment, to a number of small-scale developments. The thesis examines the paradigm and its suitability to construction of large and complex software systems by focusing on the development of two software systems of significant complexity. Throughout the thesis we propose a number of improvements and modifications that should be applied to the paradigm when developing or reengineering large and complex software systems. The discussion in the thesis covers various aspects of software development that relate to Stepwise Feature Introduction. More specifically, we evaluate the paradigm based on the common practices of object-oriented programming and design and agile development methodologies. We also outline the strategy to testing systems built with the paradigm of Stepwise Feature Introduction.

Real-time Image-based RGB-D Camera Motion Tracking and Environment Mapping

In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.

Model based analysis of the post-combustion calcium looping process for carbon dioxide capture

This thesis presents a one-dimensional, semi-empirical dynamic model for the simulation and analysis of a calcium looping process for post-combustion CO2 capture. Reduction of greenhouse emissions from fossil fuel power production requires rapid actions including the development of efficient carbon capture and sequestration technologies. The development of new carbon capture technologies can be expedited by using modelling tools. Techno-economical evaluation of new capture processes can be done quickly and cost-effectively with computational models before building expensive pilot plants. Post-combustion calcium looping is a developing carbon capture process which utilizes fluidized bed technology with lime as a sorbent. The main objective of this work was to analyse the technological feasibility of the calcium looping process at different scales with a computational model. A one-dimensional dynamic model was applied to the calcium looping process, simulating the behaviour of the interconnected circulating fluidized bed reactors. The model incorporates fundamental mass and energy balance solvers to semi-empirical models describing solid behaviour in a circulating fluidized bed and chemical reactions occurring in the calcium loop. In addition, fluidized bed combustion, heat transfer and core-wall layer effects were modelled. The calcium looping model framework was successfully applied to a 30 kWth laboratory scale and a pilot scale unit 1.7 MWth and used to design a conceptual 250 MWth industrial scale unit. Valuable information was gathered from the behaviour of a small scale laboratory device. In addition, the interconnected behaviour of pilot plant reactors and the effect of solid fluidization on the thermal and carbon dioxide balances of the system were analysed. The scale-up study provided practical information on the thermal design of an industrial sized unit, selection of particle size and operability in different load scenarios.