Analysis and validation of space averaged drag model for numerical simulations of gas-solid flows in fluidized beds

This thesis presents an approach for formulating and validating a space averaged drag model for coarse mesh simulations of gas-solid flows in fluidized beds using the two-fluid model. Proper modeling for fluid dynamics is central in understanding any industrial multiphase flow. The gas-solid flows in fluidized beds are heterogeneous and usually simulated with the Eulerian description of phases. Such a description requires the usage of fine meshes and small time steps for the proper prediction of its hydrodynamics. Such constraint on the mesh and time step size results in a large number of control volumes and long computational times which are unaffordable for simulations of large scale fluidized beds. If proper closure models are not included, coarse mesh simulations for fluidized beds do not give reasonable results. The coarse mesh simulation fails to resolve the mesoscale structures and results in uniform solids concentration profiles. For a circulating fluidized bed riser, such predicted profiles result in a higher drag force between the gas and solid phase and also overestimated solids mass flux at the outlet. Thus, there is a need to formulate the closure correlations which can accurately predict the hydrodynamics using coarse meshes. This thesis uses the space averaging modeling approach in the formulation of closure models for coarse mesh simulations of the gas-solid flow in fluidized beds using Geldart group B particles. In the analysis of formulating the closure correlation for space averaged drag model, the main parameters for the modeling were found to be the averaging size, solid volume fraction, and distance from the wall. The closure model for the gas-solid drag force was formulated and validated for coarse mesh simulations of the riser, which showed the verification of this modeling approach. Coarse mesh simulations using the corrected drag model resulted in lowered values of solids mass flux. Such an approach is a promising tool in the formulation of appropriate closure models which can be used in coarse mesh simulations of large scale fluidized beds.

Computational chemistry studies of wood-derived lignans

This thesis is based on computational chemistry studies on lignans, focusing on the naturally occurring lignan hydroxymatairesinol (HMR) (Papers I II) and on TADDOL-like conidendrin-based chiral 1,4-diol ligands (LIGNOLs) (Papers III V). A complete quantum chemical conformational analysis on HMR was previously conducted by Dr. Antti Taskinen. In the works reported in this thesis, HMR was further studied by classical molecular dynamics (MD) simulations in aqueous solution including torsional angle analysis, quantum chemical solvation e ect study by the COnductorlike Screening MOdel (COSMO), and hydrogen bond analysis (Paper I), as well as from a catalytic point of view including protonation and deprotonation studies at di erent levels of theory (Paper II). The computational LIGNOL studies in this thesis constitute a multi-level deterministic structural optimization of the following molecules: 1,1-diphenyl (2Ph), two diastereomers of 1,1,4-triphenyl (3PhR, 3PhS), 1,1,4,4-tetraphenyl (4Ph) and 1,1,4,4-tetramethyl (4Met) 1,4-diol (Paper IV) and a conformational solvation study applying MD and COSMO (Paper V). Furthermore, a computational study on hemiketals in connection with problems in the experimental work by Docent Patrik Eklund's group synthesizing the LIGNOLs based on natural products starting from HMR, is shortly described (Paper III).

Oxidation rates of carbon and nitrogen in char residues from solid fuels

Computational fluid dynamics (CFD) modeling is an important tool in designing new combustion systems. By using CFD modeling, entire combustion systems can be modeled and the emissions and the performance can be predicted. CFD modeling can also be used to develop new and better combustion systems from an economical and environmental point of view. In CFD modeling of solid fuel combustion, the combustible fuel is generally treated as single fuel particles. One of the limitations with the CFD modeling concerns the sub-models describing the combustion of single fuel particles. Available models in the scientific literature are in many cases not suitable as submodels for CFD modeling since they depend on a large number of input parameters and are computationally heavy. In this thesis CFD-applicable models are developed for the combustion of single fuel particles. The single particle models can be used to improve the combustion performance in various combustion devices or develop completely new technologies. The investigated fields are oxidation of carbon (C) and nitrogen (N) in char residues from solid fuels. Modeled char-C oxidation rates are compared to experimental oxidation rates for a large number of pulverized solid fuel chars under relevant combustion conditions. The experiments have been performed in an isothermal plug flow reactor operating at 1123-1673 K and 3-15 vol.% O2. In the single particle model, the char oxidation is based on apparent kinetics and depends on three fuel specific parameters: apparent pre-exponential factor, apparent activation energy, and apparent reaction order. The single particle model can be incorporated as a sub-model into a CFD code. The results show that the modeled char oxidation rates are in good agreement with experimental char oxidation rates up to around 70% of burnout. Moreover, the results show that the activation energy and the reaction order can be assumed to be constant for a large number of bituminous coal chars under conditions limited by the combined effects of chemical kinetics and pore diffusion. Based on this, a new model based on only one fuel specific parameter is developed (Paper III). The results also show that reaction orders of bituminous coal chars and anthracite chars differ under similar conditions (Paper I and Paper II); reaction orders of bituminous coal chars were found to be one, while reaction orders of anthracite chars were determined to be zero. This difference in reaction orders has not previously been observed in the literature and should be considered in future char oxidation models. One of the most frequently used comprehensive char oxidation models could not explain the difference in the reaction orders. In the thesis (Paper II), a modification to the model is suggested in order to explain the difference in reaction orders between anthracite chars and bituminous coal chars. Two single particle models are also developed for the NO formation and reduction during the oxidation of single biomass char particles. In the models the char-N is assumed to be oxidized to NO and the NO is partly reduced inside the particle. The first model (Paper IV) is based on the concentration gradients of NO inside and outside the particle and the second model is simplified to such an extent that it is based on apparent kinetics and can be incorporated as a sub-model into a CFD code (Paper V). Modeled NO release rates from both models were in good agreement with experimental measurements from a single particle reactor of quartz glass operating at 1173-1323 K and 3-19 vol.% O2. In the future, the models can be used to reduce NO emissions in new combustion systems.

Pumping system optimization tool

Pumping systems account for over 20 % of all electricity consumption in European industry. Optimization and correct design of such systems is important and there is a reasonable amount of unrealized energy saving potential in old pumping systems. The energy efficiency and therefore also the energy consumption of a pumping system heavily depends on the correct dimensioning and selection of devices. In this work, a graphical optimization tool for pumping systems is developed in Matlab programming language. The tool selects optimal pump, electrical motor and frequency converter for existing pumping process and calculates the life cycle costs of the whole system. The tool could be used as an aid when choosing the machinery and to analyze the energy consumption of existing systems. Results given by the tool are compared to the results of laboratory tests. The selection of pump and motor works reasonably well, but the frequency converter selection still needs development

Storytelling as a branding tool in social media

Tutkimuksen tavoitteena on kuvailla tarinankerrontaa brändin rakennuksen välineenä, ja selvittää mitkä ovat tarinankerronnan erityispiirteet sosiaalisessa mediassa. Aikaisempien teorioiden ja julkaisujen avulla kootaan viitekehys joka osoittaa käsitteiden vaikutukset toisiinsa. Tutkimus osoittaa tarinankerronnan vaikuttavan vahvistavasti kaikkiin brändipääoman ulottuvuuksiin, lähinnä tunteita herättävien ja muistettavuutta lisäävien ominaisuuksiensa ansiosta. Empiirisessä osiossa selvitetään laadullisen sisällönanalyysin keinoin kuinka yleistä brändien tarinankerronta tällä hetkellä on, ja kuvaillaan millaisia tarinoita yritykset kertovat. Aineisto koostuu sadan suosituimman brändin Facebookissa jakamista videomuotoisista tarinoista. Tutkimus osoitti, että brändien tarinankerronta sosiaalisessa mediassa on toistaiseksi melko vähäistä. Tarinat voidaan luokitella kirjallisuudesta tuttujen tarinatyyppien mukaisesti. Suurin osa brändien esittämistä tarinoista pyrkii synnyttämään yleisössä ihailun ja nostalgian tunteita, mutta useat tarinat myös sisältävät humoristisia piirteitä.

Jatkuvan äänitehojakautuman algoritmi pitkien käytävien äänikenttien mallintamiseen

JÄKÄLA-algoritmi (Jatkuvan Äänitehojakautuman algoritmi Käytävien Äänikenttien LAskentaan) ja sen NUMO- ja APPRO-laskentayhtälöt perustuvat käytävällä olevan todellisen äänilähteen kuvalähteiden symmetriaan. NUMO on algoritmin numeerisen ratkaisun ja APPRO likiarvoratkaisun laskentayhtälö. Algoritmia johdettaessa oletettiin, että absorptiomateriaali oli jakautunut tasaisesti käytävän ääntä heijastaville pinnoille. Suorakaiteen muotoisen käytävän kuvalähdetason muunto jatkuvaksi äänitehojakautumaksi sisältää kolme muokkausvaihetta. Aluksi suorakaiteen kuvalähdetaso muunnetaan neliön muotoiseksi. Seuraavaksi neliön muotoisen kuvalähdetason samanarvoiset kuvalähteet siirretään koordinaattiakselille diskreetiksi kuvalähdejonoksi. Lopuksi kuvalähdejono muunnetaan jatkuvaksi äänitehojakautumaksi, jolloin käytävän vastaanottopisteen äänenpainetaso voidaan laskea integroimalla jatkuvan äänitehojakautuman yli. JÄKÄLA-algoritmin validiteetin toteamiseksi käytettiin testattua kaupallista AKURI-ohjelmaa. AKURI-ohjelma antoi myös hyvän käsityksen siitä, miten NUMO- ja APPRO-yhtälöillä lasketut arvot mahdollisesti eroavat todellisilla käytävillä mitatuista arvoista. JÄKÄLA-algoritmin NUMO- ja APPRO-yhtälöitä testattiin myös vertaamalla niiden antamia tuloksia kolmen erityyppisen käytävän äänenpainetasomittauksiin. Tässä tutkimuksessa on osoitettu, että akustisen kuvateorian pohjalta on mahdollista johtaa laskenta-algoritmi, jota voidaan soveltaa pitkien käytävien äänikenttien pika-arvioinnissa paikan päällä. Sekä teoreettinen laskenta että käytännön äänenpainetasomittaukset todellisilla käytävillä osoittivat, että JÄKÄLA-algoritmin yhtälöiden ennustustarkkuus oli erinomainen ideaalikäytävillä ja hyvä niillä todellisilla käytävillä, joilla ei ollut ääntä heijastavia rakenteita. NUMO- ja APPRO-yhtälöt näyttäisivät toimivan hyvin käytävillä, joiden poikkileikkaus oli lähes neliön muotoinen ja joissa pintojen suurin absorptiokerroin oli korkeintaan kymmenen kertaa pienintä absorptiokerrointa suurempi. NUMO- ja APPRO-yhtälöiden suurin puute on, etteivät ne ota huomioon pintojen erilaisia absorptiokertoimia eivätkä esineistä heijastuvia ääniä. NUMO- ja APPRO- laskentayhtälöt poikkesivat mitatuista arvoista eniten käytävillä, joilla kahden vastakkaisen pinnan absorptiokerroin oli hyvin suuri ja toisen pintaparin hyvin pieni, ja käytävillä, joissa oli massiivisia, ääntä heijastavia pilareita ja palkkeja. JÄKÄLA-algoritmin NUMO- ja APPRO-yhtälöt antoivat tutkituilla käytävillä kuitenkin selvästi tarkempia arvoja kuin Kuttruffin likiarvoyhtälö ja tilastollisen huoneakustiikan perusyhtälö. JÄKÄLA-algoritmin laskentatarkkuutta on testattu vain neljällä todellisella käytävällä. Algoritmin kehittämiseksi tulisi jatkossa käytävän vastakkaisia pintoja ja niiden absorptiokertoimia käsitellä laskennassa pareittain. Algoritmin validiteetin varmistamiseksi on mittauksia tehtävä lisää käytävillä, joiden absorptiomateriaalien jakautumat poikkeavat toisistaan.

Regulation of self-renewal and detection of karyotypic changes of pluripotent human embryonic stem cells

Human embryonic stem cells are pluripotent cells capable of renewing themselves and differentiating to specialized cell types. Because of their unique regenerative potential, pluripotent cells offer new opportunities for disease modeling, development of regenerative therapies, and treating diseases. Before pluripotent cells can be used in any therapeutic applications, there are numerous challenges to overcome. For instance, the key regulators of pluripotency need to be clarified. In addition, long term culture of pluripotent cells is associated with the accumulation of karyotypic abnormalities, which is a concern regarding the safe use of the cells for therapeutic purposes. The goal of the work presented in this thesis was to identify new factors involved in the maintenance of pluripotency, and to further characterize molecular mechanisms of selected candidate genes. Furthermore, we aimed to set up a new method for analyzing genomic integrity of pluripotent cells. The experimental design applied in this study involved a wide range of molecular biology, genome-wide, and computational techniques to study the pluripotency of stem cells and the functions of the target genes. In collaboration with instrument and reagent company Perkin Elmer, KaryoliteTM BoBsTM was implemented for detecting karyotypic changes of pluripotent cells. Novel genes were identified that are highly and specifically expressed in hES cells. Of these genes, L1TD1 and POLR3G were chosen for further investigation. The results revealed that both of these factors are vital for the maintenance of pluripotency and self-renewal of the hESCs. KaryoliteTM BoBsTM was validated as a novel method to detect karyotypic abnormalities in pluripotent stem cells. The results presented in this thesis offer significant new information on the regulatory networks associated with pluripotency. The results will facilitate in understanding developmental and cancer biology, as well as creating stem cell based applications. KaryoliteTM BoBsTM provides rapid, high-throughput, and cost-efficient tool for screening of human pluripotent cell cultures.

Model-based estimation of liquid flows in the blast furnace hearth and taphole

This thesis presents a set of methods and models for estimation of iron and slag flows in the blast furnace hearth and taphole. The main focus was put on predicting taphole flow patterns and estimating the effects of various taphole conditions on the drainage behavior of the blast furnace hearth. All models were based on a general understanding of the typical tap cycle of an industrial blast furnace. Some of the models were evaluated on short-term process data from the reference furnace. A computational fluid dynamics (CFD) model was built and applied to simulate the complicated hearth flows and thus to predict the regions of the hearth exerted to erosion under various operating conditions. Key boundary variables of the CFD model were provided by a simplified drainage model based on the first principles. By examining the evolutions of liquid outflow rates measured from the furnace studied, the drainage model was improved to include the effects of taphole diameter and length. The estimated slag delays showed good agreement with the observed ones. The liquid flows in the taphole were further studied using two different models and the results of both models indicated that it is more likely that separated flow of iron and slag occurs in the taphole when the liquid outflow rates are comparable during tapping. The drainage process was simulated with an integrated model based on an overall balance analysis: The high in-furnace overpressure can compensate for the resistances induced by the liquid flows in the hearth and through the taphole. Finally, a recently developed multiphase CFD model including interfacial forces between immiscible liquids was developed and both the actual iron-slag system and a water-oil system in laboratory scale were simulated. The model was demonstrated to be a useful tool for simulating hearth flows for gaining understanding of the complex phenomena in the drainage of the blast furnace.

Indoor Localization Solutions for a Marine Industry Augmented Reality Tool

In this report are described means for indoor localization in special, challenging circum-stances in marine industry. The work has been carried out in MARIN project, where a tool based on mobile augmented reality technologies for marine industry is developed. The tool can be used for various inspection and documentation tasks and it is aimed for improving the efficiency in design and construction work by offering the possibility to visualize the newest 3D-CAD model in real environment. Indoor localization is needed to support the system in initialization of the accurate camera pose calculation and auto-matically finding the right location in the 3D-CAD model. The suitability of each indoor localization method to the specific environment and circumstances is evaluated.

Modeling of fireside deposit formation in two industrial furnaces

Fireside deposits can be found in many types of utility and industrial furnaces. The deposits in furnaces are problematic because they can reduce heat transfer, block gas paths and cause corrosion. To tackle these problems, it is vital to estimate the influence of deposits on heat transfer, to minimize deposit formation and to optimize deposit removal. It is beneficial to have a good understanding of the mechanisms of fireside deposit formation. Numerical modeling is a powerful tool for investigating the heat transfer in furnaces, and it can provide valuable information for understanding the mechanisms of deposit formation. In addition, a sub-model of deposit formation is generally an essential part of a comprehensive furnace model. This work investigates two specific processes of fireside deposit formation in two industrial furnaces. The first process is the slagging wall found in furnaces with molten deposits running on the wall. A slagging wall model is developed to take into account the two-layer structure of the deposits. With the slagging wall model, the thickness and the surface temperature of the molten deposit layer can be calculated. The slagging wall model is used to predict the surface temperature and the heat transfer to a specific section of a super-heater tube panel with the boundary condition obtained from a Kraft recovery furnace model. The slagging wall model is also incorporated into the computational fluid dynamics (CFD)-based Kraft recovery furnace model and applied on the lower furnace walls. The implementation of the slagging wall model includes a grid simplification scheme. The wall surface temperature calculated with the slagging wall model is used as the heat transfer boundary condition. Simulation of a Kraft recovery furnace is performed, and it is compared with two other cases and measurements. In the two other cases, a uniform wall surface temperature and a wall surface temperature calculated with a char bed burning model are used as the heat transfer boundary conditions. In this particular furnace, the wall surface temperatures from the three cases are similar and are in the correct range of the measurements. Nevertheless, the wall surface temperature profiles with the slagging wall model and the char bed burning model are different because the deposits are represented differently in the two models. In addition, the slagging wall model is proven to be computationally efficient. The second process is deposit formation due to thermophoresis of fine particles to the heat transfer surface. This process is considered in the simulation of a heat recovery boiler of the flash smelting process. In order to determine if the small dust particles stay on the wall, a criterion based on the analysis of forces acting on the particle is applied. Time-dependent simulation of deposit formation in the heat recovery boiler is carried out and the influence of deposits on heat transfer is investigated. The locations prone to deposit formation are also identified in the heat recovery boiler. Modeling of the two processes in the two industrial furnaces enhances the overall understanding of the processes. The sub-models developed in this work can be applied in other similar deposit formation processes with carefully-defined boundary conditions.

Computational modeling of the properties of TiO2 nanoparticles

In this study we discuss the electronic, structural, and optical properties of titanium dioxide nanoparticles, and also the properties of Ni(II) diimine dithiolato complexes as dyes in dye-sensitized TiO2 based solar cells. The abovementioned properties have been modeled by using computational codes based on the density functional theory. The results achieved show slight evidence on the structure-dependent band gap broadening, and clear blue-shifts in absorption spectra and refractive index functions of ultra-small TiO2 particles. It is also shown that these properties are strongly dependent on the shape of the nanoparticles. Regarding the Ni(II) diimine dithiolato complexes as dyes in dye-sensitized TiO2 based solar cells, it is shown that based on the experimental electrochemical investigation and DFT studies all studied diimine derivatives could serve as potential candidates for the light harvesting, but the e ciencies of the dyes studied are not very promising.

“Development work thesis” as a tool for continuing professional education

Julkaisumaa: 158 TW TWN Taiwan

Diffusion Tensor Imaging as a Diagnostic and Research Tool: A Study on Preterm Infants

Diffusion tensor imaging (DTI) is an advanced magnetic resonance imaging (MRI) technique. DTI is based on free thermal motion (diffusion) of water molecules. The properties of diffusion can be represented using parameters such as fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, which are calculated from DTI data. These parameters can be used to study the microstructure in fibrous structure such as brain white matter. The aim of this study was to investigate the reproducibility of region-of-interest (ROI) analysis and determine associations between white matter integrity and antenatal and early postnatal growth at term age using DTI. Antenatal growth was studied using both the ROI and tract-based spatial statistics (TBSS) method and postnatal growth using only the TBSS method. The infants included to this study were born below 32 gestational weeks or birth weight less than 1,501 g and imaged with a 1.5 T MRI system at term age. Total number of 132 infants met the inclusion criteria between June 2004 and December 2006. Due to exclusion criteria, a total of 76 preterm infants (ROI) and 36 preterm infants (TBSS) were accepted to this study. The ROI analysis was quite reproducible at term age. Reproducibility varied between white matter structures and diffusion parameters. Normal antenatal growth was positively associated with white matter maturation at term age. The ROI analysis showed associations only in the corpus callosum. Whereas, TBSS revealed associations in several brain white matter areas. Infants with normal antenatal growth showed more mature white matter compared to small for gestational age infants. The gestational age at birth had no significant association with white matter maturation at term age. It was observed that good early postnatal growth associated negatively with white matter maturation at term age. Growth-restricted infants seemed to have delayed brain maturation that was not fully compensated at term, despite catchup growth.