Höyryturbiinin kanavistojen numeerinen virtauslaskenta

Diplomityössä tutkittiin Fortumin Loviisan ydinvoimalaitoksen ulosvirtauskanaviston ja suurnopeuskosteudenerottimen toimintaa, sekä selvitettiin taustalla olevaa teoriaa ja aiemmin tehtyjä tutkimuksia. Tavoitteena oli ymmärtää ja esittää laitteiden toimintaa, sekä tutkia voiko ulosvirtauskanaviston suorituskykyä parantaa geometrian muutoksilla. Työssä luotiin tutkittaville kohteille geometriat ja laskentahilat, joiden avulla simuloitiin niiden toimintaa eri käyttötilanteissa numeerisen virtauslaskennan avulla. Laskennan reunaehdot saatiin olemassa olevasta prosessimallista ja aiemmista turbiiniselvityksistä. Ulosvirtauskanaviston suorituskyky laskettiin kolmella eri lauhdutinpaineella neljällä eri geometrialla. Geometrian muutokset vaikuttivat selkeästi ulosvirtauskanaviston suorituskykyyn ja sitä saatiin parannettua. Kaksi kolmesta muutoksesta, lisäkanavat ja oikaistu vesilippa, pa-ransivat suorituskykyä. Lokinsiipien poistaminen heikensi ulosvirtauskanaviston toi-mintaa. Suurnopeuskosteudenerottimen mallintaminen jäi lähtötietojen ja ajan puutteen takia hieman tavoitteesta. Sekä ulosvirtauskanaviston että suurnopeuskosteudenerotti-men jatkotutkimusta ja mahdollisia toimenpiteitä varten saatiin arvokasta uutta tietoa.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

The estimation of tuberculosis transmission parameters using ABC and MCMC methods

The aim of this work is to apply approximate Bayesian computation in combination with Marcov chain Monte Carlo methods in order to estimate the parameters of tuberculosis transmission. The methods are applied to San Francisco data and the results are compared with the outcomes of previous works. Moreover, a methodological idea with the aim to reduce computational time is also described. Despite the fact that this approach is proved to work in an appropriate way, further analysis is needed to understand and test its behaviour in different cases. Some related suggestions to its further enhancement are described in the corresponding chapter.

Virtual Runtime Application Partitions for Resource Management in Massively Parallel Architectures

This thesis presents a novel design paradigm, called Virtual Runtime Application Partitions (VRAP), to judiciously utilize the on-chip resources. As the dark silicon era approaches, where the power considerations will allow only a fraction chip to be powered on, judicious resource management will become a key consideration in future designs. Most of the works on resource management treat only the physical components (i.e. computation, communication, and memory blocks) as resources and manipulate the component to application mapping to optimize various parameters (e.g. energy efficiency). To further enhance the optimization potential, in addition to the physical resources we propose to manipulate abstract resources (i.e. voltage/frequency operating point, the fault-tolerance strength, the degree of parallelism, and the configuration architecture). The proposed framework (i.e. VRAP) encapsulates methods, algorithms, and hardware blocks to provide each application with the abstract resources tailored to its needs. To test the efficacy of this concept, we have developed three distinct self adaptive environments: (i) Private Operating Environment (POE), (ii) Private Reliability Environment (PRE), and (iii) Private Configuration Environment (PCE) that collectively ensure that each application meets its deadlines using minimal platform resources. In this work several novel architectural enhancements, algorithms and policies are presented to realize the virtual runtime application partitions efficiently. Considering the future design trends, we have chosen Coarse Grained Reconfigurable Architectures (CGRAs) and Network on Chips (NoCs) to test the feasibility of our approach. Specifically, we have chosen Dynamically Reconfigurable Resource Array (DRRA) and McNoC as the representative CGRA and NoC platforms. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Synthesis and simulation results demonstrate VRAP significantly enhances the energy and power efficiency compared to state of the art.

A new map of Denmark, Norway, Sweden, & Moscovy shewing their present general divisions, cheif, [!] cities or towns, rivers, mountains, &c.

[N. 1:8500000].

Non-Markovian dynamics in quantum optical dephasing channels

Quantum computation and quantum communication are two of the most promising future applications of quantum mechanics. Since the information carriers used in both of them are essentially open quantum systems it is necessary to understand both quantum information theory and the theory of open quantum systems in order to investigate realistic implementations of such quantum technologies. In this thesis we consider the theory of open quantum systems from a quantum information theory perspective. The thesis is divided into two parts: review of the literature and original research. In the review of literature we present some important definitions and known results of open quantum systems and quantum information theory. We present the definitions of trace distance, two channel capacities and superdense coding capacity and give a reasoning why they can be used to represent the transmission efficiency of a communication channel. We also show derivations of some properties useful to link completely positive and trace preserving maps to trace distance and channel capacities. With the help of these properties we construct three measures of non-Markovianity and explain why they detect non-Markovianity. In the original research part of the thesis we study the non-Markovian dynamics in an experimentally realized quantum optical set-up. For general one-qubit dephasing channels we calculate the explicit forms of the two channel capacities and the superdense coding capacity. For the general two-qubit dephasing channel with uncorrelated local noises we calculate the explicit forms of the quantum capacity and the mutual information of a four-letter encoding. By using the dynamics in the experimental implementation as a set of specific dephasing channels we also calculate and compare the measures in one- and two-qubit dephasing channels and study the options of manipulating the environment to achieve revivals and higher transmission rates in superdense coding protocol with dephasing noise. Kvanttilaskenta ja kvanttikommunikaatio ovat kaksi puhutuimmista tulevaisuuden kvanttimekaniikan käytännön sovelluksista. Koska molemmissa näistä informaatio koodataan systeemeihin, jotka ovat oleellisesti avoimia kvanttisysteemejä, sekä kvantti-informaatioteorian, että avointen kvanttisysteemien tuntemus on välttämätöntä. Tässä tutkielmassa käsittelemme avointen kvanttisysteemien teoriaa kvantti-informaatioteorian näkökulmasta. Tutkielma on jaettu kahteen osioon: kirjallisuuskatsaukseen ja omaan tutkimukseen. Kirjallisuuskatsauksessa esitämme joitakin avointen kvanttisysteemien ja kvantti-informaatioteorian tärkeitä määritelmiä ja tunnettuja tuloksia. Esitämme jälkietäisyyden, kahden kanavakapasiteetin ja superdense coding -kapasiteetin määritelmät ja esitämme perustelun sille, miksi niitä voidaan käyttää kuvaamaan kommunikointikanavan lähetystehokkuutta. Näytämme myös todistukset kahdelle ominaisuudelle, jotka liittävät täyspositiiviset ja jäljensäilyttävät kuvaukset jälkietäisyyteen ja kanavakapasiteetteihin. Näiden ominaisuuksien avulla konstruoimme kolme epä-Markovisuusmittaa ja perustelemme, miksi ne havaitsevat dynamiikan epä-Markovisuutta. Oman tutkimuksen osiossa tutkimme epä-Markovista dynamiikkaa kokeellisesti toteutetussa kvanttioptisessa mittausjärjestelyssä. Yleisen yhden qubitin dephasing-kanavan tapauksessa laskemme molempien kanavakapasiteettien ja superdense coding -kapasiteetin eksplisiittiset muodot. Yleisen kahden qubitin korreloimattomien ympäristöjen dephasing-kanavan tapauksessa laskemme yhteisen informaation lausekkeen nelikirjaimisessa koodauksessa ja kvanttikanavakapasiteetin. Käyttämällä kokeellisen mittajärjestelyn dynamiikkoja esimerkki dephasing-kanavina me myös laskemme konstruoitujen epä-Markovisuusmittojen arvot ja vertailemme niitä yksi- ja kaksi-qubitti-dephasing-kanavissa. Lisäksi käyttäen kokeellisia esimerkkikanavia tutkimme, kuinka ympäristöä manipuloimalla superdense coding –skeemassa voidaan saada yhteinen informaatio ajoittain kasvamaan tai saavuttaa kaikenkaikkiaan korkeampi lähetystehokkuus.

Scaling analysis of small break experiments in PACTEL

The purpose of this thesis is to study the scalability of small break LOCA experiments. The study is performed on the experimental data, as well as on the results of thermal hydraulic computation performed on TRACE code. The SBLOCA experiments were performed on PACTEL facility situated at LUT. The temporal scaling of the results was done by relating the total coolant mass in the system with the initial break mass flow and using the quotient to scale the experiment time. The results showed many similarities in the behaviour of pressure and break mass flow between the experiments.

A new map of Denmark, Norway, Sweden & Moscovy, shewing their present general divisions, cheif, cities or towns, rivers, mountains, &c.: dedicated to his highness William Duke of Glocester

0-meridiaani Lontoo: Koordinaattiasteikko: W15°-E85°, N74°30'-48°.