Power Consumption in Carbon Capture and Storage Systems (CCS) and Possibilities to Reduce Power Consumption with Variable Speed Drives

The aim of this master´s thesis is to study which processes increase the auxiliary power consumption in carbon capture and storage processes and if it is possible to reduce the auxiliary power consumption with variable speed drives. Also the cost of carbon capture and storage is studied. Data about auxiliary power consumption in carbon capture is gathered from various studies and estimates made by various research centres. Based on these studies a view is presented how the power auxiliary power consumption is divided between different processes in carbon capture processes. In a literary study, the operation of three basic carbon capture systems is described. Also different methods to transport carbon dioxide and carbon dioxide storage options are described in this section. At the end of the thesis processes that consume most of the auxiliary power are defined and possibilities to reduce the auxiliary power consumption are evaluated. Cost of carbon capture, transport and storage are also evaluated at this point and in the case that the carbon capture and storage systems are fully deployed. According to the results, it can be estimated what are the processes are where variable speed drives can be used and what kind of cost and power consumption reduction could be achieved. Results also show how large a project carbon capture and storage is if it is fully deployed.

Energy efficiency parameters in variable speed drives

The main purpose of this thesis is to measure and evaluate how accurately the current energy saving calculation in ABB’s new variable speed drive ACS850 works. The main topic of this thesis is energy-efficiency parameters. At the beginning of this thesis centrifugal pump, squirrel cage motor and variable speed drive, including some equations related to them, are being introduced. Also methods of throttling control and variable speed drive control of centrifugal pumps are being introduced. These subjects are introduced because the energy saving calculation in ACS850 is related to the centrifugal pumps usually driven by squirrel cage motors. The theory also includes short section about specific energy of pumping. Before measurements the current energy saving calculation of ACS850 is being introduced and analyzed. The measurements part includes introduction of measuring equipment, measurement results, summary and analysis of the measurements. At the end of this thesis a proposal for an improvement to the current energy saving calculation is being introduced and few proposals are made for new energy-efficiency parameters, which could be added to variable speed drives. At the end are also thoughts

Ratiomuuttujat ja näennäinen korrelaatio

Eri tieteenalojen tutkijat ovat kiistelleet jo yli vuosisadan ajan ratiomuodossa olevien muuttujien käytön vaikutuksista korrelaatio- ja regressioanalyysien tuloksiin ja niiden oikeaan tulkintaan. Strategiatutkimuksen piirissä aiheeseen ei ole kuitenkaan kiinnitetty suuresti huomiota. Tämä on yllättävää, sillä ratiomuuttujat ovat hyvin yleisesti käytettyjä empiirisen strategiatutkimuksen piirissä. Tässä työssä luodaan katsaus ratiomuuttujien ympärillä käytyyn debattiin. Lisäksi selvitetään artikkelikatsauksen avulla niiden käytön yleisyyttä nykypäivän strategiatutkimuksessa. Työssä tutkitaan Monte Carlo –simulaatioiden avulla ratiomuuttujien ominaisuuksien vaikutuksia korrelaatio- ja regressioanalyysin tuloksiin erityisesti yhteisen nimittäjän tapauksissa.

Active du/dt Filtering for Variable-Speed AC Drives

An oscillating overvoltage has become a common phenomenon at the motor terminal in inverter-fed variable-speed drives. The problem has emerged since modern insulated gate bipolar transistors have become the standard choice as the power switch component in lowvoltage frequency converter drives. Theovervoltage phenomenon is a consequence of the pulse shape of inverter output voltage and impedance mismatches between the inverter, motor cable, and motor. The overvoltages are harmful to the electric motor, and may cause, for instance, insulation failure in the motor. Several methods have been developed to mitigate the problem. However, most of them are based on filtering with lossy passive components, the drawbacks of which are typically their cost and size. In this doctoral dissertation, application of a new active du/dt filtering method based on a low-loss LC circuit and active control to eliminate the motor overvoltages is discussed. The main benefits of the method are the controllability of the output voltage du/dt within certain limits, considerably smaller inductances in the filter circuit resulting in a smaller physical component size, and excellent filtering performance when compared with typical traditional du/dt filtering solutions. Moreover, no additional components are required, since the active control of the filter circuit takes place in the process of the upper-level PWM modulation using the same power switches as the inverter output stage. Further, the active du/dt method will benefit from the development of semiconductor power switch modules, as new technologies and materials emerge, because the method requires additional switching in the output stage of the inverter and generation of narrow voltage pulses. Since additional switching is required in the output stage, additional losses are generated in the inverter as a result of the application of the method. Considerations on the application of the active du/dt filtering method in electric drives are presented together with experimental data in order to verify the potential of the method.

Analysis of patterns in mining time series using Qlucore

Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.

Country Risk and Market Reactions to Earnings Announcements: Evidence from Finnish Stock Markets

The objective of this thesis is to examine the market reaction around earnings announcements in Finnish stock markets. The aim is to find out whether the extreme market conditions during the financial crisis are reflected in stock prices as a stronger reaction. In addition to this, the purpose is to investigate how extensively Finnish listed companies report the country segmentation of revenues in their interim reports and whether the country risk is having a significant impact on perceived market reaction. The sample covers all companies listed in Helsinki stock exchange at 1.1.2010 and these companies’ interim reports from the first quarter of 2008 to last quarter of 2009. Final sample consists of 81 companies and 630 firm-quarter observations. The data sample has been divided in two parts, of which country risk sample contains 17 companies and 127 observations and comparison sample covers 66 companies and 503 observations. Research methodologies applied in this thesis are event study and cross-sectional regression analysis. Empirical results indicate that the market reaction occurs mainly during the announcement day and is slightly stronger in case of positive earnings surprises than the reactions observed in previous studies. In case of negative earnings surprises no significant differences can be observed. In case of country risk sample and negative earnings surprise market reaction is negative already in advance of the disclosure contrary to comparison sample. In case of positive surprise no differences can be observed. Country risk variable developed during this study seems to explain only minor part of the market reaction.

Accounting Beta Measuring Systematic Risk: Empirical Evidence from the Finnish Markets

The main purpose of this study is to examine whether accounting-based variables can be used to measure systematic risk of a company using Finnish data. When the fundamental sources of systematic risk are known, companies are able to manage these risks and increase company value. Accounting beta was formed based on OLS regression models. Theoretical background for the study was based on the findings of studies according to which business risk, financial risk, operating risk and growth risk can be theoretically regarded as determinants of the systematic risk. The results reveal that accounting variables describe systematic risk of a company. The accounting beta is found to be particularly sensitive to the changes in the risk components. The investigation is confidential until 15.10.2012.

Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

Motivational Influences on Transfer: Dimensions and Boundary Conditions

The focus of this dissertation is the motivational influences on transfer in higher education and professional training contexts. To estimate these motivational influences, the dissertation includes seven individual studies that are structured in two parts. Part I, Dimensions, aims at identifying the dimensionality of motivation to transfer and its structural relations with training-related antecedents and outcomes. Part II, Boundary Conditions, aims at testing the predictive validity of motivation theories used in contemporary training research under different study conditions. Data in this dissertation was gathered from multi-item questionnaires, which were analyzed differently in Part I and Part II. Studies in Part I employed exploratory and confirmatory factor analysis, structural equation modeling, partial least squares (PLS) path modeling, and mediation analysis. Studies in Part II used artifact distribution meta-analysis, (nested) subgroup analysis, and weighted least squares (WLS) multiple regression. Results demonstrate that motivation to transfer can be conceptualized as a three-dimensional construct, including autonomous motivation to transfer, controlled motivation to transfer, and intention to transfer, given a theoretical framework informed by expectancy theory, self-determination theory, and the theory of planned behavior. Results also demonstrate that a range of boundary conditions moderates motivational influences on transfer. To test the predictive validity of expectancy theory, social cognitive theory, and the theory of goal orientations under different study settings, a total of 17 boundary conditions were meta-analyzed, including age; assessment criterion; assessment source; attendance policy; collaboration among trainees; computer support; instruction; instrument used to measure motivation; level of education; publication type; social training context; SS/SMC bias; study setting; survey modality; type of knowledge being trained; use of a control group; and work context. Together, the findings cumulated in this thesis support the basic premise that motivation is centrally important for transfer, but that motivational influences need to be understood from a more differentiated perspective than commonly found in the literature, in order to account for several dimensions and boundary conditions. The results of this dissertation across the seven individual studies are reflected in terms of their implications for theory development and their significance for training evaluation and the design of training environments. Limitations and directions to take in future research are discussed.

Patenttien vaikutus suomalaisten pörssiyritysten markkina-arvoon - reaalioptiosovellutus

Tutkielman tavoitteena oli tutkia onko patenteilla positiivinen vaikutus yrityksen markkina-arvoon. Aihetta tutkittiin reaalioptionäkökulmasta: miten patentit voidaan nähdä reaalioptioiden ilmentymänä ja millainen vaikutus niillä on yrityksen suoriutumiseen. Lisäksi tutkittiin onko patenttien vaikutuksessa toimialakohtaisia eroja. Tavoitteena oli myös selvittää onko patenttien vaikutus erilainen talouden eri suhdanteissa. Empiriana tutkimuksessa olivat suomalaiset pörssiyritykset ja niiden Suomeen myönnetyt patentit. Tutkittavana ajanjaksona oli 2001–2010. Tutkimusongelmista johdettuja hypoteeseja testattiin regressioanalyysien avulla. Selitettävänä muuttujana oli yrityksen Tobin’s q ja selittävänä muuttujana yrityksen voimassa olleiden patenttien ja tasearvon suhdeluku. Kontrollimuuttujina käytettiin vuotta ja toimialaa. Tulokseksi saatiin, että patenteilla on ollut positiivinen vaikutus suomalaisten pörssiyritysten markkina-arvoon 2000-luvulla. Varsinkin teknologian ja perusmateriaalien toimialoilla yhteys oli vahvempi kuin muilla toimialoilla. Saadut tulokset ovat yhdenmukaisia aiempien tutkimusten kanssa. Aineiston erityispiirteet toivat tutkimukseen omat haasteensa, jotka vaikuttivat muun muassa toimialaryhmien muodostamiseen sekä makroekonomisen ympäristön merkityksen tutkimiseen.

Non-Markovian Dynamics in Continuous Variable Quantum Systems

The present manuscript represents the completion of a research path carried forward during my doctoral studies in the University of Turku. It contains information regarding my scientific contribution to the field of open quantum systems, accomplished in collaboration with other scientists. The main subject investigated in the thesis is the non-Markovian dynamics of open quantum systems with focus on continuous variable quantum channels, e.g. quantum Brownian motion models. Non-Markovianity is here interpreted as a manifestation of the existence of a flow of information exchanged by the system and environment during the dynamical evolution. While in Markovian systems the flow is unidirectional, i.e. from the system to the environment, in non-Markovian systems there are time windows in which the flow is reversed and the quantum state of the system may regain coherence and correlations previously lost. Signatures of a non-Markovian behavior have been studied in connection with the dynamics of quantum correlations like entanglement or quantum discord. Moreover, in the attempt to recognisee non-Markovianity as a resource for quantum technologies, it is proposed, for the first time, to consider its effects in practical quantum key distribution protocols. It has been proven that security of coherent state protocols can be enhanced using non-Markovian properties of the transmission channels. The thesis is divided in two parts: in the first part I introduce the reader to the world of continuous variable open quantum systems and non-Markovian dynamics. The second part instead consists of a collection of five publications inherent to the topic.

Health-related quality of life in school children: validation of instrument, child self assessment, parent-proxy assessment and school nursing documentation of health check-ups

The aims of this study were to validate an international Health-Related Quality of Life (HRQL) instrument, to describe child self and parent-proxy assessed HRQL at child age 10 to 12 and to compare child self assessments with parent-proxy assessments and school nursing documentation. The study is part of the Schools on the Move –research project. In phase one, a cross-cultural translation and validation process was performed to develop a Finnish version of Pediatric Quality of Life Inventory™ 4.0 (PedsQL™ 4.0). The process included a two-way translation, cognitive interviews (children n=7, parents n=5) and a survey (children n=1097, parents n=999). In phase two, baseline and follow-up surveys (children n=986, parents n=710) were conducted to describe and compare the child self and parent-proxy assessed HRQL in school children between the ages 10 and 12. Phase three included two separate data, school nurse documented patient records (children n=270) and a survey (children n=986). The relation between child self assessed HRQL and school nursing documentation was evaluated. Validity and reliability of the Finnish version of PedsQL™ 4.0 was good (Child Self Report α=0.91, Parent-Proxy Report α=0.88). Children reported lower HRQL scores at the emotional (mean 76/80) than the physical (mean 85/89) health domains and significantly lower scores at the age of 10 than 12 (dMean=4, p=<0.001). Agreement between child self and parent-proxy assessment was fragile (r=0,4, p=<0.001) but increased as the child grew from age 10 to 12 years. At health check-ups, school nurses documented frequently children’s physical health, such as growth (97%) and posture (98/99%) but seldom emotional issues, such as mood (2/7%). The PedsQLTM 4.0 is a valid instrument to assess HRQL in Finnish school children although future research is recommended. Children’s emotional wellbeing needs future attention. HRQL scores increase during ages between childhood and adolescence. Concordance between child self and parent-proxy assessed HRQL is low. School nursing documentation, related to child health check-ups, is not in line with child self assessed HRQL and emotional issues need more attention.

Software for design of experiments and response modelling of cake ltration applications

Filtration is a widely used unit operation in chemical engineering. The huge variation in the properties of materials to be ltered makes the study of ltration a challenging task. One of the objectives of this thesis was to show that conventional ltration theories are di cult to use when the system to be modelled contains all of the stages and features that are present in a complete solid/liquid separation process. Furthermore, most of the ltration theories require experimental work to be performed in order to obtain critical parameters required by the theoretical models. Creating a good overall understanding of how the variables a ect the nal product in ltration is somewhat impossible on a purely theoretical basis. The complexity of solid/liquid separation processes require experimental work and when tests are needed, it is advisable to use experimental design techniques so that the goals can be achieved. The statistical design of experiments provides the necessary tools for recognising the e ects of variables. It also helps to perform experimental work more economically. Design of experiments is a prerequisite for creating empirical models that can describe how the measured response is related to the changes in the values of the variable. A software package was developed that provides a ltration practitioner with experimental designs and calculates the parameters for linear regression models, along with the graphical representation of the responses. The developed software consists of two software modules. These modules are LTDoE and LTRead. The LTDoE module is used to create experimental designs for di erent lter types. The lter types considered in the software are automatic vertical pressure lter, double-sided vertical pressure lter, horizontal membrane lter press, vacuum belt lter and ceramic capillary action disc lter. It is also possible to create experimental designs for those cases where the variables are totally user de ned, say for a customized ltration cycle or di erent piece of equipment. The LTRead-module is used to read the experimental data gathered from the experiments, to analyse the data and to create models for each of the measured responses. Introducing the structure of the software more in detail and showing some of the practical applications is the main part of this thesis. This approach to the study of cake ltration processes, as presented in this thesis, has been shown to have good practical value when making ltration tests.

Novel Regression Methods For Spectral Data

Singular Value Decomposition (SVD), Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) are some of the mathematical pre- liminaries that are discussed prior to explaining PLS and PCR models. Both PLS and PCR are applied to real spectral data and their di erences and similarities are discussed in this thesis. The challenge lies in establishing the optimum number of components to be included in either of the models but this has been overcome by using various diagnostic tools suggested in this thesis. Correspondence analysis (CA) and PLS were applied to ecological data. The idea of CA was to correlate the macrophytes species and lakes. The di erences between PLS model for ecological data and PLS for spectral data are noted and explained in this thesis. i