959 resultados para CFD FLUENT fluidodinamica computazionale reazione chimica eterogenea reattori agitati
Resumo:
The transport of macromolecules, such as low-density lipoprotein (LDL), and their accumulation in the layers of the arterial wall play a critical role in the creation and development of atherosclerosis. Atherosclerosis is a disease of large arteries e.g., the aorta, coronary, carotid, and other proximal arteries that involves a distinctive accumulation of LDL and other lipid-bearing materials in the arterial wall. Over time, plaque hardens and narrows the arteries. The flow of oxygen-rich blood to organs and other parts of the body is reduced. This can lead to serious problems, including heart attack, stroke, or even death. It has been proven that the accumulation of macromolecules in the arterial wall depends not only on the ease with which materials enter the wall, but also on the hindrance to the passage of materials out of the wall posed by underlying layers. Therefore, attention was drawn to the fact that the wall structure of large arteries is different than other vessels which are disease-resistant. Atherosclerosis tends to be localized in regions of curvature and branching in arteries where fluid shear stress (shear rate) and other fluid mechanical characteristics deviate from their normal spatial and temporal distribution patterns in straight vessels. On the other hand, the smooth muscle cells (SMCs) residing in the media layer of the arterial wall respond to mechanical stimuli, such as shear stress. Shear stress may affect SMC proliferation and migration from the media layer to intima. This occurs in atherosclerosis and intimal hyperplasia. The study of blood flow and other body fluids and of heat transport through the arterial wall is one of the advanced applications of porous media in recent years. The arterial wall may be modeled in both macroscopic (as a continuous porous medium) and microscopic scales (as a heterogeneous porous medium). In the present study, the governing equations of mass, heat and momentum transport have been solved for different species and interstitial fluid within the arterial wall by means of computational fluid dynamics (CFD). Simulation models are based on the finite element (FE) and finite volume (FV) methods. The wall structure has been modeled by assuming the wall layers as porous media with different properties. In order to study the heat transport through human tissues, the simulations have been carried out for a non-homogeneous model of porous media. The tissue is composed of blood vessels, cells, and an interstitium. The interstitium consists of interstitial fluid and extracellular fibers. Numerical simulations are performed in a two-dimensional (2D) model to realize the effect of the shape and configuration of the discrete phase on the convective and conductive features of heat transfer, e.g. the interstitium of biological tissues. On the other hand, the governing equations of momentum and mass transport have been solved in the heterogeneous porous media model of the media layer, which has a major role in the transport and accumulation of solutes across the arterial wall. The transport of Adenosine 5´-triphosphate (ATP) is simulated across the media layer as a benchmark to observe how SMCs affect on the species mass transport. In addition, the transport of interstitial fluid has been simulated while the deformation of the media layer (due to high blood pressure) and its constituents such as SMCs are also involved in the model. In this context, the effect of pressure variation on shear stress is investigated over SMCs induced by the interstitial flow both in 2D and three-dimensional (3D) geometries for the media layer. The influence of hypertension (high pressure) on the transport of lowdensity lipoprotein (LDL) through deformable arterial wall layers is also studied. This is due to the pressure-driven convective flow across the arterial wall. The intima and media layers are assumed as homogeneous porous media. The results of the present study reveal that ATP concentration over the surface of SMCs and within the bulk of the media layer is significantly dependent on the distribution of cells. Moreover, the shear stress magnitude and distribution over the SMC surface are affected by transmural pressure and the deformation of the media layer of the aorta wall. This work reflects the fact that the second or even subsequent layers of SMCs may bear shear stresses of the same order of magnitude as the first layer does if cells are arranged in an arbitrary manner. This study has brought new insights into the simulation of the arterial wall, as the previous simplifications have been ignored. The configurations of SMCs used here with elliptic cross sections of SMCs closely resemble the physiological conditions of cells. Moreover, the deformation of SMCs with high transmural pressure which follows the media layer compaction has been studied for the first time. On the other hand, results demonstrate that LDL concentration through the intima and media layers changes significantly as wall layers compress with transmural pressure. It was also noticed that the fraction of leaky junctions across the endothelial cells and the area fraction of fenestral pores over the internal elastic lamina affect the LDL distribution dramatically through the thoracic aorta wall. The simulation techniques introduced in this work can also trigger new ideas for simulating porous media involved in any biomedical, biomechanical, chemical, and environmental engineering applications.
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This thesis gathers knowledge about ongoing high-temperature reactor projects around the world. Methods for calculating coolant flow and heat transfer inside a pebble-bed reactor core are also developed. The thesis begins with the introduction of high-temperature reactors including the current state of the technology. Process heat applications that could use the heat from a high-temperature reactor are also introduced. A suitable reactor design with data available in literature is selected for the calculation part of the thesis. Commercial computational fluid dynamics software Fluent is used for the calculations. The pebble-bed is approximated as a packed-bed, which causes sink terms to the momentum equations of the gas flowing through it. A position dependent value is used for the packing fraction. Two different models are used to calculate heat transfer. First a local thermal equilibrium is assumed between the gas and solid phases and a single energy equation is used. In the second approach, separate energy equations are used for the phases. Information about steady state flow behavior, pressure loss, and temperature distribution in the core is obtained as results of the calculations. The effect of inlet mass flow rate to pressure loss is also investigated. Data found in literature and the results correspond each other quite well, considered the amount of simplifications in the calculations. The models developed in this thesis can be used to solve coolant flow and heat transfer in a pebble-bed reactor, although additional development and model validation is needed for better accuracy and reliability.
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Tässä diplomityössä optimoitiin nelivaiheinen 1 MWe höyryturbiinin prototyyppimalli evoluutioalgoritmien avulla sekä tutkittiin optimoinnista saatuja kustannushyötyjä. Optimoinnissa käytettiin DE – algoritmia. Optimointi saatiin toimimaan, mutta optimoinnissa käytetyn laskentasovelluksen (semiempiirisiin yhtälöihin perustuvat mallit) luonteesta johtuen optimoinnin tarkkuus CFD – laskennalla suoritettuun tarkastusmallinnukseen verrattuna oli jonkin verran toivottua pienempi. Tulosten em. epätarkkuus olisi tuskin ollut vältettävissä, sillä ongelma johtui puoliempiirisiin laskentamalleihin liittyvistä lähtöoletusongelmista sekä epävarmuudesta sovitteiden absoluuttisista pätevyysalueista. Optimoinnin onnistumisen kannalta tällainen algebrallinen mallinnus oli kuitenkin välttämätöntä, koska esim. CFD-laskentaa ei olisi mitenkään voitu tehdä jokaisella optimointiaskeleella. Optimoinnin aikana ongelmia esiintyi silti konetehojen riittävyydessä sekä sellaisen sopivan rankaisumallin löytämisessä, joka pitäisi algoritmin matemaattisesti sallitulla alueella, muttei rajoittaisi liikaa optimoinnin edistymistä. Loput ongelmat johtuivat sovelluksen uutuudesta sekä täsmällisyysongelmista sovitteiden pätevyysalueiden käsittelyssä. Vaikka optimoinnista saatujen tulosten tarkkuus ei ollut aivan tavoitteen mukainen, oli niillä kuitenkin koneensuunnittelua edullisesti ohjaava vaikutus. DE – algoritmin avulla suoritetulla optimoinnilla saatiin turbiinista noin 2,2 % enemmän tehoja, joka tarkoittaa noin 15 000 € konekohtaista kustannushyötyä. Tämä on yritykselle erittäin merkittävä konekohtainen kustannushyöty. Loppujen lopuksi voitaneen sanoa, etteivät evoluutioalgoritmit olleet parhaimmillaan prototyyppituotteen optimoinnissa. Evoluutioalgoritmeilla teknisten laitteiden optimoinnissa piilee valtavasti mahdollisuuksia, mutta se vaatii kypsän sovelluskohteen, joka tunnetaan jo entuudestaan erinomaisesti tai on yksinkertainen ja aukottomasti laskettavissa.
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The objective of this thesis is to shed light on the vertical vibration of granular materials for potential interest in the power generation industry. The main focus is investigating the drag force and frictional resistance that influence the movement of a granular material (in the form of glass beads) contained in a vessel, which is subjected to sinusoidal oscillation. The thesis is divided into three parts: theoretical analysis, experiments and computer simulations. The theoretical part of this study presents the underlying physical phenomena of the vibration of granular materials. Experiments are designed to determine fundamental parameters that contribute to the behavior of vibrating granular media. Numerical simulations include the use of three different software applications: FLUENT, LS-DYNA and ANSYS Workbench. The goal of these simulations is to test theoretical and semiempirical models for granular materials in order to validate their compatibility with the experimental findings, to assist in predicting their behavior, and to estimate quantities that are hard to measure in laboratory.
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Soodakattilan sulakeon epästationaarinen käyttäytyminen sekä keon pitkä jäähtymisaika alasajon jälkeen ovat aiheuttaneet ongelmia kattilan taloudellisessa käytettävyydessä. Keon käyttäytymisestä on luotu CFD-malleja, joiden tavoitteena on havainnollistaa keon lämpötilajakaumaa ja rakennetta. Mallien ongelmana on se, että niissä huomioidaan vain keon aktiivinen pintakerros. Keon sisäosan rakennetta ja siinä tapahtuvia prosesseja ei toistaiseksi tunneta kunnolla luotettavan, koko keon kattavan mallin luomiseen. Tässä työssä tutkittiin sulakeon käytön aikana havaittuja muutosilmiöitä, jotka vaikuttavat keon rakenteeseen ja ominaisuuksiin sekä tutkittiin ilmiöiden taustalla olevia tekijöitä. Näitä tekijöitä ovat keon sisässä tapahtuvat kemialliset ja fyysiset prosessit, jotka aiheuttavat muutoksia niin lämpöteknisesti kuin fyysisesti sekä ulkoapäin tulevat tekijät, jotka aiheutuvat ajotilanteiden seurauksena tapahtuvista muutoksista. Työn kokeellisena osana luotiin sulakeon jäähtymismalli käyttäen 1-dimensionaalista ADL-mallia. Mallin pohjana käytettiin StoraEnso Oy:ltä Oulun soodakattilan sulakeosta saatua mittausraporttia. ADL-mallin avulla luotiin keon jäähtymiskäyrät lämpötilan ja syvyyden funktiona. Saadut käyrät täsmäsivät hyvin mittausraportin tuloksiin. Mallin avulla keolle saatiin muodostettua energiatase, jonka tuloksena keosta 12 tunnin aikana poistuva lämpövirta pinnalla oli noin 9.8kW/m2 ja pinnan lämmönsiirtokerroin 58.3W/m²°C. Pohjan poistuvaksi lämpövirraksi saatiin 14.1kW/m2 ja lämmönsiirtokertoimeksi 75.4W/m²°C. Termiseksi diffuusiokertoimeksi saatiin 3.9•10-7m²/s.
Resumo:
From the boiler design point of view, it is imperative to know and understand the operation of the boiler. Since comprehensive measurement of a large furnace is impossible, the furnace can be modeled in order to study its behavior and phenomena. This requires the used model to be validated to correspond with the physical furnace behavior. In this thesis, a three dimensional furnace model is validated to match a bituminous coal utilizing, supercritical once-through circulating fluidized bed combustor based on measurement data. The validated model is used for analyzing the furnace heat transfer. Other heat transfer analysis methods are energy balance method based on tube surface temperature measurements and a method based on measured temperature difference between the tube crest and the fin. The latter method was developed in the thesis using Fluent-software. In the theory part, literature is reviewed and the fundamental aspects of circulating fluidized bed are discussed. These aspects are solid particle behavior in fluidization known as hydrodynamics, behavior of fuel and combustion and heat transfer. Fundamental aspects of modeling are also presented.
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Once the seed has germinated, the plant is forced to face all the environmental changes in its habitat. In order to survive, plants have evolved a number of different acclimation systems. The primary reaction behind plant growth and development is photosynthesis. Photosynthesis captures solar energy and converts it into chemical form. Photosynthesis in turn functions under the control of environmental cues, but is also affected by the growth, development, and metabolic state of a plant. The availability of solar energy fluctuates continuously, requiring non-stop adjustment of photosynthetic efficiency in order to maintain the balance between photosynthesis and the requirements and restrictions of plant metabolism. Tight regulation is required, not only to provide sufficient energy supply but also to prevent the damage caused by excess energy. The very first reaction of photosynthesis is splitting of water into the form of oxygen, hydrogen, and electrons. This most fundamental reaction of life is run by photosystem II (PSII), and the energy required for the reaction is collected by the light harvesting complex II (LHCII). Several proteins of the PSII-LHCII complex are reversibly phosphorylated according to the energy balance between photosynthesis and metabolism. Thylakoid protein phosphorylation has been under extensive investigation for over 30 years, yet the physiological role of phosphorylation remains elusive. Recently, the kinases behind the phosphorylation of PSII-LHCII proteins (STN7 and STN8) were identified and the knockout mutants of these kinases became available, providing powerful tools to elucidate the physiological role of PSII-LHCII phosphorylation. In my work I have used the stn7 and stn8 mutants in order to clarify the role of PSII-LHCII phosphorylation in regulation and protection of the photosynthetic machinery according to environmental cues. I show that STN7- dependent PSII-LHCII protein phosphorylation is required to balance the excitation energy distribution between PSII and PSI especially under low light intensities when the excitation energy transfer from LHC to PSII and PSI is efficient. This mechanism differs from traditional light quality-induced “state 1” – “state 2” transition and ensures fluent electron transfer from PSII to PSI under low light, yet having highest physiological relevance under fluctuating light intensity. STN8-dependent phosphorylation of PSII proteins, in turn, is required for fluent turn-over of photodamaged PSII complexes and has the highest importance upon prolonged exposure of the photosynthetic apparatus to excess light.
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Fluent health information flow is critical for clinical decision-making. However, a considerable part of this information is free-form text and inabilities to utilize it create risks to patient safety and cost-effective hospital administration. Methods for automated processing of clinical text are emerging. The aim in this doctoral dissertation is to study machine learning and clinical text in order to support health information flow.First, by analyzing the content of authentic patient records, the aim is to specify clinical needs in order to guide the development of machine learning applications.The contributions are a model of the ideal information flow,a model of the problems and challenges in reality, and a road map for the technology development. Second, by developing applications for practical cases,the aim is to concretize ways to support health information flow. Altogether five machine learning applications for three practical cases are described: The first two applications are binary classification and regression related to the practical case of topic labeling and relevance ranking.The third and fourth application are supervised and unsupervised multi-class classification for the practical case of topic segmentation and labeling.These four applications are tested with Finnish intensive care patient records.The fifth application is multi-label classification for the practical task of diagnosis coding. It is tested with English radiology reports.The performance of all these applications is promising. Third, the aim is to study how the quality of machine learning applications can be reliably evaluated.The associations between performance evaluation measures and methods are addressed,and a new hold-out method is introduced.This method contributes not only to processing time but also to the evaluation diversity and quality. The main conclusion is that developing machine learning applications for text requires interdisciplinary, international collaboration. Practical cases are very different, and hence the development must begin from genuine user needs and domain expertise. The technological expertise must cover linguistics,machine learning, and information systems. Finally, the methods must be evaluated both statistically and through authentic user-feedback.
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Computational methods for the calculation of dynamical properties of fluids might consider the system as a continuum or as an assembly of molecules. Molecular dynamics (MD) simulation includes molecular resolution, whereas computational fluid dynamics (CFD) considers the fluid as a continuum. This work provides a review of hybrid methods MD/CFD recently proposed in the literature. Theoretical foundations, basic approaches of computational methods, and dynamical properties typically calculated by MD and CFD are first presented in order to appreciate the similarities and differences between these two methods. Then, methods for coupling MD and CFD, and applications of hybrid simulations MD/CFD, are presented.
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The objective of this thesis was to study the removal of gases from paper mill circulation waters experimentally and to provide data for CFD modeling. Flow and bubble size measurements were carried out in a laboratory scale open gas separation channel. Particle Image Velocimetry (PIV) technique was used to measure the gas and liquid flow fields, while bubble size measurements were conducted using digital imaging technique with back light illumination. Samples of paper machine waters as well as a model solution were used for the experiments. The PIV results show that the gas bubbles near the feed position have the tendency to escape from the circulation channel at a faster rate than those bubbles which are further away from the feed position. This was due to an increased rate of bubble coalescence as a result of the relatively larger bubbles near the feed position. Moreover, a close similarity between the measured slip velocities of the paper mill waters and that of literature values was obtained. It was found that due to dilution of paper mill waters, the observed average bubble size was considerably large as compared to the average bubble sizes in real industrial pulp suspension and circulation waters. Among the studied solutions, the model solution has the highest average drag coefficient value due to its relatively high viscosity. The results were compared to a 2D steady sate CFD simulation model. A standard Euler-Euler k-ε turbulence model was used in the simulations. The channel free surface was modeled as a degassing boundary. From the drag models used in the simulations, the Grace drag model gave velocity fields closest to the experimental values. In general, the results obtained from experiments and CFD simulations are in good qualitative agreement.
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Pyörivien sähkökoneiden suunnittelussa terminen suunnittelu on yhtä tärkeää kuin sähköinen ja mekaaninen suunnittelukin. Tässä diplomityössä tarkoituksena on kehittää ilmajäähdytteisten kestomagneettigeneraattorien laskentaan soveltuva lämmönsiirtymismalli, jolla staattorin lämpötilajakauma voitaisiin selvittää. Kehitetty lämmönsiirtymismalli perustuu kolmiulotteiseen äärellisen erotuksen (finite difference) menetelmään. Malli ottaa huomioon lämmönjohtumisen staattorin aktiiviosissa ja konvektion jäähdytysilmavirtaan. Mallissa on myös yksinkertainen painehäviölaskenta jäähdytysjärjestelmän komponenttien mitoittamista varten. Laskentamallilla lasketaan esimerkkitapauksena 4,3 MW:n kestomagneettigeneraattorin jäähdytystä eri toimintapisteissä. Tuloksia verrataan CFD-mallinnuksen antamiin tuloksiin sekä kokeellisten mittausten antamiin tuloksiin.
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Supersonic axial turbine stages typically exhibit lower efficiencies than subsonic axial turbine stages. One reason for the lower efficiency is the occurrence of shock waves. With higher pressure ratios the flow inside the turbine becomes relatively easily supersonic if there is only one turbine stage. Supersonic axial turbines can be designed in smaller physical size compared to subsonic axial turbines of same power. This makes them good candidates for turbochargers in large diesel engines, where space can be a limiting factor. Also the production costs are lower for a supersonic axial turbine stage than for two subsonic stages. Since supersonic axial turbines are typically low reaction turbines, they also create lower axial forces to be compensated with bearings compared to high reaction turbines. The effect of changing the stator-rotor axial gap in a small high (rotational) speed supersonic axial flow turbine is studied in design and off-design conditions. Also the effect of using pulsatile mass flow at the supersonic stator inlet is studied. Five axial gaps (axial space between stator and rotor) are modeled using threedimensional computational fluid dynamics at the design and three axial gaps at the off-design conditions. Numerical reliability is studied in three independent studies. An additional measurement is made with the design turbine geometry at intermediate off-design conditions and is used to increase the reliability of the modelling. All numerical modelling is made with the Navier-Stokes solver Finflo employing Chien’s k ¡ ² turbulence model. The modelling of the turbine at the design and off-design conditions shows that the total-to-static efficiency of the turbine decreases when the axial gap is increased in both design and off-design conditions. The efficiency drops almost linearily at the off-design conditions, whereas the efficiency drop accelerates with increasing axial gap at the design conditions. The modelling of the turbine stator with pulsatile inlet flow reveals that the mass flow pulsation amplitude is decreased at the stator throat. The stator efficiency and pressure ratio have sinusoidal shapes as a function of time. A hysteresis-like behaviour is detected for stator efficiency and pressure ratio as a function of inlet mass flow, over one pulse period. This behaviour arises from the pulsatile inlet flow. It is important to have the smallest possible axial gap in the studied turbine type in order to maximize the efficiency. The results for the whole turbine can also be applied to some extent in similar turbines operating for example in space rocket engines. The use of a supersonic stator in a pulsatile inlet flow is shown to be possible.
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Tämä diplomityö perustuu Lappeenrannan teknillisen yliopiston Uusiutuvien energiajärjestelmien laboratorion koelaitteistoon, jolla tutkitaan voimakkaan savukaasunkierrätyksen ja kuumailmapolton soveltuvuutta pienen kokoluokan energiantuotantoprosesseihin. Työn teoriaosassa esitellään tavanomaisesta palamisesta eroavaa kuumailmapolttoa ja tarkastellaan sen ominaisuuksia. Myös työssä käytetyn tutkimusmenetelmän, numeerisen virtauslaskennan, periaatteita ja ominaisuuksia tarkastellaan. Työssä tutkitaan numeerisella virtausmallinnuksella kuumailmapolttolaitteiston virtauskentän käyttäytymistä, kun takaisin tulipesään kierrätettävän savukaasun määrä sekä tulipesän lämpöhäviöiden suuruus vaihtelevat. Virtauskentän tarkastelu on tärkeää, sillä palamisilman ja kierrätetyn savukaasun täytyy sekoittua kuumailmapolton aikaansaamiseksi. Työn virtausmallinnus suoritettiin Finflo-virtausratkaisijalla kaksiulotteisena palamisreaktioita mallintamatta. Vaikka työssä käytetyt mallit olivat kaksiulotteisia ja niissä käytettiin yksinkertaistuksia, virtausten käyttäytymisestä tulipesässä saatiin olennaista tietoa, jota voidaan mahdollisesti hyödyntää jatkotutkimuksissa.
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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.
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Monte Carlo -reaktorifysiikkakoodit nykyisin käytettävissä olevilla laskentatehoilla tarjoavat mielenkiintoisen tavan reaktorifysiikan ongelmien ratkaisuun. Neljännen sukupolven ydinreaktoreissa käytettävät uudet rakenteet ja materiaalit ovat haasteellisia nykyisiin reaktoreihin suunnitelluille laskentaohjelmille. Tässä työssä Monte Carlo -reaktorifysiikkakoodi ja CFD-koodi yhdistetään kytkettyyn laskentaan kuulakekoreaktorissa, joka on yksi korkealämpötilareaktorityyppi. Työssä käytetty lähestymistapa on uutta maailmankin mittapuussa ajateltuna.