Insulation System in an Integrated Motor Compressor

A high-speed and high-voltage solid-rotor induction machine provides beneficial features for natural gas compressor technology. The mechanical robustness of the machine enables its use in an integrated motor-compressor. The technology uses a centrifugal compressor, which is mounted on the same shaft with the high-speed electrical machine driving it. No gearbox is needed as the speed is determined by the frequency converter. The cooling is provided by the process gas, which flows through the motor and is capable of transferring the heat away from the motor. The technology has been used in the compressors in the natural gas supply chain in the central Europe. New areas of application include natural gas compressors working at the wellheads of the subsea gas reservoir. A key challenge for the design of such a motor is the resistance of the stator insulation to the raw natural gas from the well. The gas contains water and heavy hydrocarbon compounds and it is far harsher than the sales gas in the natural gas supply network. The objective of this doctoral thesis is to discuss the resistance of the insulation to the raw natural gas and the phenomena degrading the insulation. The presence of partial discharges is analyzed in this doctoral dissertation. The breakdown voltage of the gas is measured as a function of pressure and gap distance. The partial discharge activity is measured on small samples representing the windings of the machine. The electrical field behavior is also modeled by finite element methods. Based on the measurements it has been concluded that the discharges are expected to disappear at gas pressures above 4 – 5 bar. The disappearance of discharges is caused by the breakdown strength of the gas, which increases as the pressure increases. Based on the finite element analysis, the physical length of a discharge seen in the PD measurements at atmospheric pressure was approximated to be 40 – 120 m. The chemical aging of the insulation when exposed to raw natural gas is discussed based on a vast set of experimental tests with the gas mixture representing the real gas mixture at the wellhead. The mixture was created by mixing dry hydrocarbon gas, heavy hydrocarbon compounds, monoethylene glycol, and water. The mixture was chosen to be more aggressive by increasing the amount of liquid substances. Furthermore, the temperature and pressure were increased, which resulted in accelerated test conditions. The time required to detect severe degradation was thus decreased. The test program included a comparison of materials, an analysis of the e ects of di erent compounds in the gas mixture, namely water and heavy hydrocarbons, on the aging, an analysis of the e ects of temperature and exposure duration, and also an analysis on the e ect of sudden pressure changes on the degradation of the insulating materials. It was found in the tests that an insulation consisting of mica, glass, and epoxy resin can tolerate the raw natural gas, but it experiences some degradation. The key material in the composite insulation is the resin, which largely defines the performance of the insulation system. The degradation of the insulation is mostly determined by the amount of gas mixture di used into it. The di usion was seen to follow Fick’s second law, but the coe cients were not accurately defined. The di usion was not sensitive to temperature, but it was dependent upon the thermodynamic state of the gas mixture, in other words, the amounts of liquid components in the gas. The weight increase observed was mostly related to heavy hydrocarbon compounds, which act as plasticizers in the epoxy resin. The di usion of these compounds is determined by the crosslink density of the resin. Water causes slight changes in the chemical structure, but these changes do not significantly contribute to the aging phenomena. Sudden changes in pressure can lead to severe damages in the insulation, because the motion of the di used gas is able to create internal cracks in the insulation. Therefore, the di usion only reduces the mechanical strength of the insulation, but the ultimate breakdown can potentially be caused by a sudden drop in the pressure of the process gas.

Loviisan ydinvoimalaitoksen todennäköisyyspohjaisen riskianalyysin tason 2 epävarmuustarkastelut

Diplomityössä tarkastellaan Loviisan ydinvoimalaitoksen todennäköisyyspohjaisen riskianalyysin tason 2 epävarmuuksia. Tason 2 riskitutkimuksissa tutkitaan ydinvoimalaitosonnettomuuksia, joiden seurauksena osa reaktorin radioaktiivisista aineista vapautuu ympäristöön. Näiden tutkimuksien päätulos on suuren päästön vuotuinen taajuus ja se on pääosin todelliseen laitoshistoriaan perustuva tilastollinen odotusarvo. Tämän odotusarvon uskottavuutta voidaan parantaa huomioimalla merkittävimmät laskentaan liittyvät epävarmuudet. Epävarmuuksia laskentaan aiheutuu muiden muassa vakavan reaktorionnettomuuden ilmiöistä, turvallisuusjärjestelmien laitteista, inhimillisistä toiminnoista sekä luotettavuusmallin määrittelemättömistä osista. Diplomityössä kuvataan, kuinka epävarmuustarkastelut integroidaan osaksi Loviisan ydinvoimalaitoksen todennäköisyyspohjaisia riskianalyysejä. Tämä toteutetaan diplomityössä kehitetyillä apuohjelmilla PRALA:lla ja PRATU:lla, joiden avulla voidaan lisätä laitoshistorian perusteella muodostetut epävarmuusparametrit osaksi riskianalyysien luotettavuusdataa. Lisäksi diplomityössä on laskettu laskentaesimerkkinä Loviisan ydinvoimalaitoksen suuren päästön vuotuisen taajuuden vaihtelua kuvaava luottamusväli. Tämä laskentaesimerkki pohjautuu pääosin konservatiivisiin epävarmuusarvioihin, ei todellisiin tilastollisiin epävarmuuksiin. Laskentaesimerkin tulosten perusteella Loviisan suuren päästön taajuudella on laaja vaihteluväli; virhekertoimeksi saatiin 8,4 nykyisillä epävarmuusparametreilla. Suuren päästön taajuuden luottamusväliä voidaan kuitenkin tulevaisuudessa supistaa, kun hyödynnetään todelliseen laitoshistoriaan perustuvia epävarmuusparametreja.

Bayesian methods for estimation, optimization and experimental design

Mathematical models often contain parameters that need to be calibrated from measured data. The emergence of efficient Markov Chain Monte Carlo (MCMC) methods has made the Bayesian approach a standard tool in quantifying the uncertainty in the parameters. With MCMC, the parameter estimation problem can be solved in a fully statistical manner, and the whole distribution of the parameters can be explored, instead of obtaining point estimates and using, e.g., Gaussian approximations. In this thesis, MCMC methods are applied to parameter estimation problems in chemical reaction engineering, population ecology, and climate modeling. Motivated by the climate model experiments, the methods are developed further to make them more suitable for problems where the model is computationally intensive. After the parameters are estimated, one can start to use the model for various tasks. Two such tasks are studied in this thesis: optimal design of experiments, where the task is to design the next measurements so that the parameter uncertainty is minimized, and model-based optimization, where a model-based quantity, such as the product yield in a chemical reaction model, is optimized. In this thesis, novel ways to perform these tasks are developed, based on the output of MCMC parameter estimation. A separate topic is dynamical state estimation, where the task is to estimate the dynamically changing model state, instead of static parameters. For example, in numerical weather prediction, an estimate of the state of the atmosphere must constantly be updated based on the recently obtained measurements. In this thesis, a novel hybrid state estimation method is developed, which combines elements from deterministic and random sampling methods.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Frequency-Domain and Wide-Pulse Time-Domain Measurements of Lanthanide Luminescence and Lanthanide-Based Resonance Energy Transfer

Resonance energy transfer (RET) is a non-radiative transfer of the excitation energy from the initially excited luminescent donor to an acceptor. The requirements for the resonance energy transfer are: i) the spectral overlap between the donor emission spectrum and the acceptor absorption spectrum, ii) the close proximity of the donor and the acceptor, and iii) the suitable relative orientations of the donor emission and the acceptor absorption transition dipoles. As a result of the RET process the donor luminescence intensity and the donor lifetime are decreased. If the acceptor is luminescent, a sensitized acceptor emission appears. The rate of RET depends strongly on the donor–acceptor distance (r) and is inversely proportional to r6. The distance dependence of RET is utilized in binding assays. The proximity requirement and the selective detection of the RET-modified emission signal allow homogeneous separation free assays. The term lanthanide-based RET is used when luminescent lanthanide compounds are used as donors. The long luminescence lifetimes, the large Stokes’ shifts and the intense, sharply-spiked emission spectra of the lanthanide donors offer advantages over the conventional organic donor molecules. Both the organic lanthanide chelates and the inorganic up-converting phosphor (UCP) particles have been used as donor labels in the RET based binding assays. In the present work lanthanide luminescence and lanthanide-based resonance energy transfer phenomena were studied. Luminescence lifetime measurements had an essential role in the research. Modular frequency-domain and time-domain luminometers were assembled and used successfully in the lifetime measurements. The frequency-domain luminometer operated in the low frequency domain ( 100 kHz) and utilized a novel dual-phase lock-in detection of the luminescence. One of the studied phenomena was the recently discovered non-overlapping fluorescence resonance energy transfer (nFRET). The studied properties were the distance and temperature dependences of nFRET. The distance dependence was found to deviate from the Förster theory and a clear temperature dependence was observed whereas conventional RET was completely independent of the temperature. Based on the experimental results two thermally activated mechanisms were proposed for the nFRET process. The work with the UCP particles involved the measurement of the luminescence properties of the UCP particles synthesized in our laboratory. The goal of the UCP particle research is to develop UCP donor labels for binding assays. In the present work the effect of the dopant concentrations and the core–shell structure on the total up-conversion luminescence intensity, the red–green emission ratio, and the luminescence lifetime was studied. Also the non-radiative nature of the energy transfer from the UCP particle donors to organic acceptors was demonstrated for the first time in aqueous environment and with a controlled donor–acceptor distance.

Testing Futures Market Efficiency and Optimal Hedge Ratio Estimation: Evidence from Futures and Options on RTS

This study investigates futures market efficiency and optimal hedge ratio estimation. First, cointegration between spot and futures prices is studied using Johansen method, with two different model specifications. If prices are found cointegrated, restrictions on cointegrating vector and adjustment coefficients are imposed, to account for unbiasedness, weak exogeneity and prediction hypothesis. Second, optimal hedge ratios are estimated using static OLS, and time-varying DVEC and CCC models. In-sample and out-of-sample results for one, two and five period ahead are reported. The futures used in thesis are RTS index, EUR/RUB exchange rate and Brent oil, traded in Futures and options on RTS.(FORTS) For in-sample period, data points were acquired from start of trading of each futures contract, RTS index from August 2005, EUR/RUB exchange rate March 2009 and Brent oil October 2008, lasting till end of May 2011. Out-of-sample period covers start of June 2011, till end of December 2011. Our results indicate that all three asset pairs, spot and futures, are cointegrated. We found RTS index futures to be unbiased predictor of spot price, mixed evidence for exchange rate, and for Brent oil futures unbiasedness was not supported. Weak exogeneity results for all pairs indicated spot price to lead in price discovery process. Prediction hypothesis, unbiasedness and weak exogeneity of futures, was rejected for all asset pairs. Variance reduction results varied between assets, in-sample in range of 40-85 percent and out-of sample in range of 40-96 percent. Differences between models were found small, except for Brent oil in which OLS clearly dominated. Out-of-sample results indicated exceptionally high variance reduction for RTS index, approximately 95 percent.

Development of Cost Estimation with Feedback Information in EPCM Business

Target company of this study is a large machinery company, which is, inter alia, engaged in energy and pulp engineering, procurement and construction management (EPCM) supply business. The main objective of this study was to develop cost estimation of the target company by providing more accurate, reliable and up-to-date information through enterprise resource planning (ERP) system. Another objective was to find cost-effective methods to collect total cost of ownership information to support more informed supplier selection decision making. This study is primarily action-oriented, but also constructive, and it can be divided in two sections: theoretical literature review and empirical study on the abovementioned part of the target company’s business. Development of information collection is, in addition to literature review, based on nearly 30 qualitative interviews of employees at various organizational units, functions and levels at the target company. At the core of development was to make initial data more accurate, reliable and available, a necessary prerequisite for informed use of the information. Certain development suggestions and paths were presented in order to regain confidence in ERP system as information source by reorganizing work breakdown structure and by complementing mere cost information with quantitative, technical and scope information. Several methods to use the information ever more effectively were also discussed. While implementation of the development suggestions outreached the scope of this study, it was forwarded in test environment and interest groups.

The probabilistic risk analysis of external hazards of an interim storage for spent nuclear fuel

Tässä diplomityössä tehtiin Olkiluodon ydinvoimalaitoksella sijaitsevan käytetyn ydinpolttoaineen allasvarastointiin perustuvan välivaraston todennäköisyysperustainen ulkoisten uhkien riskianalyysi. Todennäköisyysperustainen riskianalyysi (PRA) on yleisesti käytetty riskien tunnistus- ja lähestymistapa ydinvoimalaitoksella. Työn tarkoituksena oli laatia täysin uusi ulkoisten uhkien PRA-analyysi, koska Suomessa ei ole aiemmin tehty vastaavanlaisia tämän tutkimusalueen riskitarkasteluja. Riskitarkastelun motiivina ovat myös maailmalla tapahtuneiden luonnonkatastrofien vuoksi korostunut ulkoisten uhkien rooli käytetyn ydinpolttoaineen välivarastoinnin turvallisuudessa. PRA analyysin rakenne pohjautui tutkimuksen alussa luotuun metodologiaan. Analyysi perustuu mahdollisten ulkoisten uhkien tunnistamiseen pois lukien ihmisen aikaansaamat tahalliset vahingot. Tunnistettujen ulkoisten uhkien esiintymistaajuuksien ja vahingoittamispotentiaalin perusteella ulkoiset uhat joko karsittiin pois tutkimuksessa määriteltyjen karsintakriteerien avulla tai analysoitiin tarkemmin. Tutkimustulosten perusteella voitiin todeta, että tiedot hyvin harvoin tapahtuvista ulkoisista uhista ovat epätäydellisiä. Suurinta osaa näistä hyvin harvoin tapahtuvista ulkoisista uhista ei ole koskaan esiintynyt eikä todennäköisesti koskaan tule esiintymään Olkiluodon vaikutusalueella tai edes Suomessa. Esimerkiksi salaman iskujen ja öljyaltistuksen roolit ja vaikutukset erilaisten komponenttien käytettävyyteen ovat epävarmasti tunnettuja. Tutkimuksen tuloksia voidaan pitää kokonaisuudessaan merkittävinä, koska niiden perusteella voidaan osoittaa ne ulkoiset uhat, joiden vaikutuksia olisi syytä tutkia tarkemmin. Yksityiskohtaisempi tietoisuus hyvin harvoin esiintyvistä ulkoisista uhista tarkentaisi alkutapahtumataajuuksien estimaatteja.

Flexible multibody approach in bone strain estimation during physical activity:

Bone strain plays a major role as the activation signal for the bone (re)modeling process, which is vital for keeping bones healthy. Maintaining high bone mineral density reduces the chances of fracture in the event of an accident. Numerous studies have shown that bones can be strengthened with physical exercise. Several hypotheses have asserted that a stronger osteogenic (bone producing) effect results from dynamic exercise than from static exercise. These previous studies are based on short-term empirical research, which provide the motivation for justifying the experimental results with a solid mathematical background. The computer simulation techniques utilized in this work allow for non-invasive bone strain estimation during physical activity at any bone site within the human skeleton. All models presented in the study are threedimensional and actuated by muscle models to replicate the real conditions accurately. The objective of this work is to determine and present loading-induced bone strain values resulting from physical activity. It includes a comparison of strain resulting from four different gym exercises (knee flexion, knee extension, leg press, and squat) and walking, with the results reported for walking and jogging obtained from in-vivo measurements described in the literature. The objective is realized primarily by carrying out flexible multibody dynamics computer simulations. The dissertation combines the knowledge of finite element analysis and multibody simulations with experimental data and information available from medical field literature. Measured subject-specific motion data was coupled with forward dynamics simulation to provide natural skeletal movement. Bone geometries were defined using a reverse engineering approach based on medical imaging techniques. Both computed tomography and magnetic resonance imaging were utilized to explore modeling differences. The predicted tibia bone strains during walking show good agreement with invivo studies found in the literature. Strain measurements were not available for gym exercises; therefore, the strain results could not be validated. However, the values seem reasonable when compared to available walking and running invivo strain measurements. The results can be used for exercise equipment design aimed at strengthening the bones as well as the muscles during workout. Clinical applications in post fracture recovery exercising programs could also be the target. In addition, the methodology introduced in this study, can be applied to investigate the effect of weightlessness on astronauts, who often suffer bone loss after long time spent in the outer space.

Automatic system identification and optimization of centrifugal pump operation

Centrifugal pumps are a notable end-consumer of electrical energy. Typical application of a centrifugal pump is the filling or emptying of a reservoir tank, where the pump is often operated at a constant speed until the process is completed. Installing a frequency converter to control the motor substitutes the traditional fixed-speed pumping system, allows the optimization of rotational speed profile for the pumping tasks and enables the estimation of rotational speed and shaft torque of an induction motor without any additional measurements from the motor shaft. Utilization of variable-speed operation provides the possibility to decrease the overall energy consumption of the pumping task. The static head of the pumping process may change during the pumping task. In such systems, the minimum rotational speed changes during reservoir filling or emptying, and the minimum energy consumption can’t be achieved with a fixed rotational speed. This thesis presents embedded algorithms to automatically identify, optimize and monitor pumping processes between supply and destination reservoirs, and evaluates the changing static head –based optimization method.

Differential Evolution approach and parameter estimation of chaotic

Parameter estimation still remains a challenge in many important applications. There is a need to develop methods that utilize achievements in modern computational systems with growing capabilities. Owing to this fact different kinds of Evolutionary Algorithms are becoming an especially perspective field of research. The main aim of this thesis is to explore theoretical aspects of a specific type of Evolutionary Algorithms class, the Differential Evolution (DE) method, and implement this algorithm as codes capable to solve a large range of problems. Matlab, a numerical computing environment provided by MathWorks inc., has been utilized for this purpose. Our implementation empirically demonstrates the benefits of a stochastic optimizers with respect to deterministic optimizers in case of stochastic and chaotic problems. Furthermore, the advanced features of Differential Evolution are discussed as well as taken into account in the Matlab realization. Test "toycase" examples are presented in order to show advantages and disadvantages caused by additional aspects involved in extensions of the basic algorithm. Another aim of this paper is to apply the DE approach to the parameter estimation problem of the system exhibiting chaotic behavior, where the well-known Lorenz system with specific set of parameter values is taken as an example. Finally, the DE approach for estimation of chaotic dynamics is compared to the Ensemble prediction and parameter estimation system (EPPES) approach which was recently proposed as a possible solution for similar problems.

Accuracy Analysis of Frequency Converter Estimates in Diagnostic Applications

Transportation of fluids is one of the most common and energy intensive processes in the industrial and HVAC sectors. Pumping systems are frequently subject to engineering malpractice when dimensioned, which can lead to poor operational efficiency. Moreover, pump monitoring requires dedicated measuring equipment, which imply costly investments. Inefficient pump operation and improper maintenance can increase energy costs substantially and even lead to pump failure. A centrifugal pump is commonly driven by an induction motor. Driving the induction motor with a frequency converter can diminish energy consumption in pump drives and provide better control of a process. In addition, induction machine signals can also be estimated by modern frequency converters, dispensing with the use of sensors. If the estimates are accurate enough, a pump can be modelled and integrated into the frequency converter control scheme. This can open the possibility of joint motor and pump monitoring and diagnostics, thereby allowing the detection of reliability-reducing operating states that can lead to additional maintenance costs. The goal of this work is to study the accuracy of rotational speed, torque and shaft power estimates calculated by a frequency converter. Laboratory tests were performed in order to observe estimate behaviour in both steady-state and transient operation. An induction machine driven by a vector-controlled frequency converter, coupled with another induction machine acting as load was used in the tests. The estimated quantities were obtained through the frequency converter’s Trend Recorder software. A high-precision, HBM T12 torque-speed transducer was used to measure the actual values of the aforementioned variables. The effect of the flux optimization energy saving feature on the estimate quality was also studied. A processing function was developed in MATLAB for comparison of the obtained data. The obtained results confirm the suitability of this particular converter to provide accurate enough estimates for pumping applications.

Localization, Frequency, and Functions of Filled Pauses: Five American Politicians’ Use of er and erm in the Talk Show Larry King Live

Tämän pro gradu– tutkielman tavoitteena oli testata täytettyjen taukojen (er ja erm) esiintymistiheyttä, sijaintia kieliopillisessa rakenteessa sekä funktioita Kjellmerin (2003) korpus-tutkimuksessa. Materiaalina käytin viiden yhdysvaltalaisen poliitikon puhetta keskusteluohjelmasta Larry King Live. Tutkimuksessani sovelsin Kjellmerin tutkimusmenetelmiä, joita muokkasin huomattavasti suppeampaan materiaaliini sopiviksi. Lähestymistapani oli täten induktiivinen toisin kuin testatussa tutkimuksessa. Materiaalini oli tarkoituksellisesti rajattu, sillä halusin selvittää, kuvaavatko Kjellmerin laajaan materiaaliin perustuvat tutkimustulokset myös täytettyjen taukojen käyttöä suppeammassa materiaalissa. Materiaalini (kokonaisuudessaan 101 minuuttia) transkriboin ortografisesti. Analyysissäni arvioin täytettyjen taukojen esiintymistiheyden puhujakohtaisesti ja koko ryhmälle suhteuttamalla täytettyjen taukojen lukumäärän kokonaissanamäärään. Tämän jälkeen tein perinteisen kielioppianalyysin rakenteista, joita edeltää tai joissa esiintyy täytetty tauko, ja täytettyjen taukojen sijainnin perusteella luokittelin ne sana-, lauseke-, ja lausetasolle. Lopuksi analysoin täytettyjen taukojen käyttöä soveltaen Kjellmerin ehdottamia funktioita (hesitaatio, vuorottelujäsennyksen merkitseminen, huomion herättäminen ja kontaktin luominen, korostus ja korjaus) ja niiden piirteitä omaan materiaaliini. Tutkimukseni perusteella täytetyt tauot esiintyvät tutkitun viiden poliitikon puheessa suhteellisen usein. Puhujakohtaiset eroavaisuudet olivat kuitenkin huomattavat. Kieliopillisen luokitteluni mukaan sana-, lauseke- ja lausetasot eivät täysin kuvaa täytettyjen taukojen sijoittumista, sillä täytetyt tauot edelsivät mm. määre-lauseita, jotka eivät vastaa lausetasoa englannin kielessä. Materiaalini funktioanalyysi osoitti, että täytetyt tauot yleensä vastaavat yhtä tai useampaa Kjellmerin ehdottamaa funktioita. Lisäksi tutkimukseni mukaan täytetyillä tauoilla on ainakin yksi rakenteellinen funktio. Analyysini perusteella Kjellmerin tutkimustulokset ovat siis pääosin sovellettavissa suppeampaan materiaaliin. Puutteiksi hänen tutkimuksessaan osoittautuivat funktioanalyysille tärkeän kontekstuaalisen informaation puute sekä keskittyminen täytettyihin taukoihin, jotka esiintyvät vain tietyissä kielioppirakenteissa. Yleisesti voin tutkimukseni pohjalta todeta, että täytetyt tauot ovat vielä vajaasti tunnettuja ja että kieliopillisen sijoituksen ja funktioiden lisätutkimus on tarpeellista.

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.