A Practical Micro Mechanical Model Based Local Approach Methodology for the Analysis of Ductile Fracture of Welded T-Joints

This thesis concentrates on developing a practical local approach methodology based on micro mechanical models for the analysis of ductile fracture of welded joints. Two major problems involved in the local approach, namely the dilational constitutive relation reflecting the softening behaviour of material, and the failure criterion associated with the constitutive equation, have been studied in detail. Firstly, considerable efforts were made on the numerical integration and computer implementation for the non trivial dilational Gurson Tvergaard model. Considering the weaknesses of the widely used Euler forward integration algorithms, a family of generalized mid point algorithms is proposed for the Gurson Tvergaard model. Correspondingly, based on the decomposition of stresses into hydrostatic and deviatoric parts, an explicit seven parameter expression for the consistent tangent moduli of the algorithms is presented. This explicit formula avoids any matrix inversion during numerical iteration and thus greatly facilitates the computer implementation of the algorithms and increase the efficiency of the code. The accuracy of the proposed algorithms and other conventional algorithms has been assessed in a systematic manner in order to highlight the best algorithm for this study. The accurate and efficient performance of present finite element implementation of the proposed algorithms has been demonstrated by various numerical examples. It has been found that the true mid point algorithm (a = 0.5) is the most accurate one when the deviatoric strain increment is radial to the yield surface and it is very important to use the consistent tangent moduli in the Newton iteration procedure. Secondly, an assessment of the consistency of current local failure criteria for ductile fracture, the critical void growth criterion, the constant critical void volume fraction criterion and Thomason's plastic limit load failure criterion, has been made. Significant differences in the predictions of ductility by the three criteria were found. By assuming the void grows spherically and using the void volume fraction from the Gurson Tvergaard model to calculate the current void matrix geometry, Thomason's failure criterion has been modified and a new failure criterion for the Gurson Tvergaard model is presented. Comparison with Koplik and Needleman's finite element results shows that the new failure criterion is fairly accurate indeed. A novel feature of the new failure criterion is that a mechanism for void coalescence is incorporated into the constitutive model. Hence the material failure is a natural result of the development of macroscopic plastic flow and the microscopic internal necking mechanism. By the new failure criterion, the critical void volume fraction is not a material constant and the initial void volume fraction and/or void nucleation parameters essentially control the material failure. This feature is very desirable and makes the numerical calibration of void nucleation parameters(s) possible and physically sound. Thirdly, a local approach methodology based on the above two major contributions has been built up in ABAQUS via the user material subroutine UMAT and applied to welded T joints. By using the void nucleation parameters calibrated from simple smooth and notched specimens, it was found that the fracture behaviour of the welded T joints can be well predicted using present methodology. This application has shown how the damage parameters of both base material and heat affected zone (HAZ) material can be obtained in a step by step manner and how useful and capable the local approach methodology is in the analysis of fracture behaviour and crack development as well as structural integrity assessment of practical problems where non homogeneous materials are involved. Finally, a procedure for the possible engineering application of the present methodology is suggested and discussed.

Typen oksidien mittausepävarmuuden määrittäminen ilmanlaatumittauksille

Euroopan unionin direktiiveissä ja kansallisessa lainsäädännössä on asetettu tavoitteita, velvoitteita ja raja-arvoja ilmanlaadun mittauksille. Ilmanlaatua on seurattava, ilmanlaatumittaukset on tehtävä laadukkaasti sekä luotettavasti ja mittaustuloksista on tiedotettava väestölle. Mittausten epävarmuus on tunnettava ja sen on oltava alle 15 %, jotta epävarmuudelle asetettu kriteeri täyttyy. Tässä työssä perehdyttiin Euroopan unionin ilmastopolitiikkaan ja kansalliseen ilmanlaatua koskevaan lainsäädäntöön, käytiin läpi menetelmiä ja tapoja, joilla ilmanlaadusta tiedotetaan väestölle sekä selvitettiin ilmanlaadun mittausjärjestelmiä koskevia vaatimuksia. Ennen varsinaista mittausepävarmuuden selvittämistä käytiin läpi tutkimuksen kohteena olevan typen oksidien analysaattorin mittausperiaate ja merkittävimmät komponentit. Mittausepävarmuus määritettiin standardia SFS-EN 14211 noudattamalla. Mittausepävarmuuden selvittämiseksi analysaattorille tehtiin erilaisia sen toimintaa kuvaavia testejä Ilmatieteen laitoksen kalibrointilaboratoriossa. Saatujen tuloksien perusteella voitiin laskea analysaattorin mittausepävarmuus, joka tuntiraja-arvopitoisuudessa oli 15,5 % ja vuosiraja-arvopitoisuudessa 10,5 %. Kaikkia testejä ei voitu tehdä standardissa määrätyllä tavalla, joten tuloksiin pitää suhtautua kriittisesti. Tulosten perusteella mittausepävarmuus tuntiraja-arvopitoisuudessa ei aivan täytä direktiivin kriteeriä, mutta vuosiraja-arvopitoisuudessa kriteeri täyttyy (< 15 %).

Brain Dopamine and Serotonin Receptors in the Perception of Pain. Positron Emission Tomography Studies in Healthy Subjects

The role of dopamine and serotonin in spinal pain regulation is well established. However, little is known concerning the role of brain dopamine and serotonin in the perception of pain in humans. The aim of this study was to assess the potential role of brain dopamine and serotonin in determining experimental pain sensitivity in humans using positron emission tomography (PET) and psychophysical methods. A total of 39 healthy subjects participated in the study, and PET imaging was performed to assess brain dopamine D2/D3 and serotonin 5-HT_1A receptor availability. In a separate session, sensitivity to pain and touch was assessed with traditional psychophysical methods, allowing the evaluation of potential associations between D2/D3 and 5-HT_1A binding and psychophysical responses. The subjects’ responses were also analyzed according to Signal Detection Theory, which enables separate assessment of the subject’s discriminative capacity (sensory factor) and response criterion (non-sensory factor). The study found that the D2/D3 receptor binding in the right putamen was inversely correlated with pain threshold and response criterion. 5-HT_1A binding in cingulate cortex, inferior temporal gyrus and medial prefrontal cortex was inversely correlated with discriminative capacity for touch. Additionally, the response criterion for pain and intensity rating of suprathreshold pain were inversely correlated with 5-HT_1A binding in multiple brain areas. The results suggest that brain D2/D3 receptors and 5-HT_1A receptors modulate sensitivity to pain and that the pain modulatory effects may, at least partly, be attributed to influences on the response criterion. 5-HT_1A receptors are also involved in the regulation of touch by having an effect on discriminative capacity.

Testing the Random Walk Hypothesis on the Baltic Stock Markets

The purpose of the thesis is to analyze whether the returns of general stock market indices of Estonia, Latvia and Lithuania follow the random walk hypothesis (RWH), and in addition, whether they are consistent with the weak-form efficiency criterion. Also the existence of the day-of-the-week anomaly is examined in the same regional markets. The data consists of daily closing quotes of the OMX Tallinn, Riga and Vilnius total return indices for the sample period from January 3, 2000 to August 28, 2009. Moreover, the full sample period is also divided into two sub-periods. The RWH is tested by applying three quantitative methods (i.e. the Augmented Dickey-Fuller unit root test, serial correlation test and non-parametric runs test). Ordinary Least Squares (OLS) regression with dummy variables is employed to detect the day-of-the-week anomalies. The random walk hypothesis (RWH) is rejected in the Estonian and Lithuanian stock markets. The Latvian stock market exhibits more efficient behaviour, although some evidence of inefficiency is also found, mostly during the first sub-period from 2000 to 2004. Day-of-the-week anomalies are detected on every stock market examined, though no longer during the later sub-period.

Antenna Design for Contactless IC Card Applications

Contactless integrated circuit cards are one form of application of radio frequency identification. They are used in applications such as access control, identification, and payment in public transport. The contactless IC cards are passive which means that both the data and the energy are transferred to the card without contact using inductive coupling. Antenna design and optimization of the design for contactless IC cards defined by ISO/IEC14443 is studied. The basic operation principles of contactless system are presented and the structure of contactless IC card is illustrated. The structure was divided between the contactless chip and the antenna. The operation of the antenna was covered in depth and the parameters affecting to the performance of the antenna were presented. Also the different antenna technologies and connection technologies were provided. The antenna design process with the parameters and the design tools isillustrated and optimization of the design is studied. To make the design process more ideal a target of development was discovered, which was the implementation of test application. The optimization of the antenna design was presented based on the optimization criteria defined in this study. The solution for the implementation of these criteria and the effect of each criterion was found. For enhancing the performance of the antenna a focus for future study was proposed.

Regime Switching Models for Electricity Time Series that Capture Fat Tailed Distributions

In the power market, electricity prices play an important role at the economic level. The behavior of a price trend usually known as a structural break may change over time in terms of its mean value, its volatility, or it may change for a period of time before reverting back to its original behavior or switching to another style of behavior, and the latter is typically termed a regime shift or regime switch. Our task in this thesis is to develop an electricity price time series model that captures fat tailed distributions which can explain this behavior and analyze it for better understanding. For NordPool data used, the obtained Markov Regime-Switching model operates on two regimes: regular and non-regular. Three criteria have been considered price difference criterion, capacity/flow difference criterion and spikes in Finland criterion. The suitability of GARCH modeling to simulate multi-regime modeling is also studied.

Study of ligand-based virtual screening tools in computer-aided drug design

Virtual screening is a central technique in drug discovery today. Millions of molecules can be tested in silico with the aim to only select the most promising and test them experimentally. The topic of this thesis is ligand-based virtual screening tools which take existing active molecules as starting point for finding new drug candidates. One goal of this thesis was to build a model that gives the probability that two molecules are biologically similar as function of one or more chemical similarity scores. Another important goal was to evaluate how well different ligand-based virtual screening tools are able to distinguish active molecules from inactives. One more criterion set for the virtual screening tools was their applicability in scaffold-hopping, i.e. finding new active chemotypes. In the first part of the work, a link was defined between the abstract chemical similarity score given by a screening tool and the probability that the two molecules are biologically similar. These results help to decide objectively which virtual screening hits to test experimentally. The work also resulted in a new type of data fusion method when using two or more tools. In the second part, five ligand-based virtual screening tools were evaluated and their performance was found to be generally poor. Three reasons for this were proposed: false negatives in the benchmark sets, active molecules that do not share the binding mode, and activity cliffs. In the third part of the study, a novel visualization and quantification method is presented for evaluation of the scaffold-hopping ability of virtual screening tools.

Strategisen partnerin valintaprosessin erityispiirteet Venäjällä

Yritysten halu perustaa strategisia kumppanuussuhteita on kasvanut viime vuosikymmeninä. Ellram (1995) mukaan partnerisuhteita voi olla kilpailemattomien tai kilpailevien yritysten välillä ja ne voivat olla strategisia tai operationaalisia. Tämä tutkielma keskittyy kumppanin valintaan keskenään kilpailemattomien yritysten välillä. Calof & Beamish (1995) mukaan kehittyvillä markkinoilla yleisin strategisen kumppanuuden muoto kansainvälisille yrityksille on yhteisyrityksen perustaminen. Yrityksen kyky valita oikeat partnerit korostuu varsinkin Venäjällä, jossa markkinoiden volatiliteetti on suurempi kuin länsimaissa. Yrityksen etsiessä partnereita se arvioi niitä tiettyjen kriteerien mukaan. Tämän partnerin valintaprosessin erityispiirteiden määrittäminen on tämän työn tärkein tavoite. Kumppanuussuhteiden muodostaminen ei kuitenkaan ole erityisen helppoa, ja varsinkin tuottavien suhteiden luominen on haastavaa. Onnistuessaan kumppanuus kuitenkin auttaa yritystä etabloitumaan uusille markkinoille ja parantaa sen kilpailukykyä.

Choosing the optimal energy system for buildings and districts

The purpose of this master’s thesis was to develop a method to be used in the selection of an optimal energy system for buildings and districts. The term optimal energy system was defined as the energy system which best fulfils the requirements of the stakeholder on whose preferences the energy systems are evaluated. The most influential stakeholder in the process of selecting an energy system was considered to be the district developer. The selection method consisted of several steps: Definition of the district, calculating the energy consumption of the district and buildings within the district, defining suitable energy system alternatives for the district, definition of the comparing criteria, calculating the parameters of the comparing criteria for each energy system alternative and finally using a multi-criteria decision method to rank the alternatives. For the purposes of the selection method, the factors affecting the energy consumption of buildings and districts and technologies enabling the use of renewable energy were reviewed. The key element of the selection method was a multi-criteria decision making method, PROMETHEE II. In order to compare the energy system alternatives with the developed method, the comparing criteria were defined in the study. The criteria included costs, environmental impacts and technological and technical characteristics of the energy systems. Each criterion was given an importance, based on a questionnaire which was sent for the steering groups of two district development projects. The selection method was applied in two case study analyses. The results indicate that the selection method provides a viable and easy way to provide the decision makers alternatives and recommendations regarding the selection of an energy system. Since the comparison is carried out by changing the alternatives into numeric form, the presented selection method was found to exclude any unjustified preferences over certain energy systems alternatives which would affect the selection.

Hankintaprosessin optimaalinen toteutus: Case Medi-IT Oy

Tutkielman tavoitteena on löytää hankintaprosessin optimaalinen toteutustapa tutkimuksen kohdeyritykselle. Tutkielmassa kuvataan kohdeyrityksen hankintaprosessin kulku nykyisellään ja annetaan kehitysehdotuksia. Tutkielmassa pohditaan sitä, mitä osia kohdeyrityksen tulisi hankintaprosessissa suorittaa itse, ja mitä osia puolestaan tulisi ulkoistaa palveluntarjoajille. Tutkielmassa tutkitaan myös ICT-hankintoihin liittyviä erityispiirteitä ja haasteita. Lisäksi tutkielmassa käydään läpi toimittajien vertailussa käytettäviä kriteerejä. Myös hankintalain vaikutusta kohdeyrityksen toimintaan tarkastellaan lyhyesti. Tutkimuksen teoreettinen viitekehys koostuu neljästä teoria-alueesta, jotka ovat: ulkoistaminen, toimittajien luokittelu, toimittajien arviointi ja julkiset hankinnat. Teorian ja empirian välisen vuoropuhelun avulla esitetään ehdotus hankintaprosessin optimaaliseksi toteutustavaksi. Muutoksia ehdotetaan erityisesti toimijoiden väliseen roolijakoon hankintaprosessissa. Työ on luonteeltaan kvalitatiivinen tapaustutkimus. Teoriaosio perustuu kirjallisuuskatsaukseen ja empiriaosio perustuu lähinnä haastatteluihin.

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.

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.

Rovakaira Oy:n keskijänniteverkon kehittämissuunnitelma toimitusvarmuuskriteeristön näkökulmasta

Diplomityössä tavoitteena on etsiä teknistaloudellisimmat ratkaisut sekä tutkia niiden vaikutuksia sähkönjakeluverkoston käyttövarmuuteen ja luotettavuuteen toimitusvarmuuskriteeristön näkökulmasta. Lisäksi työssä esitetään uusi tunnusluku kriteeristön ylityksestä aiheutuvan haitan arvostukseen. Merkittävä osa Rovakaira Oy:n keskijänniteverkosta joudutaan uusimaan lähivuosikymmeninä teknistaloudellisen pitoajan täyttyessä. Verkon uusiminen antaa mahdollisuuden toteuttaa verkkoa nykyisiin vaatimuksiin paremmin sopivilla ratkaisuilla. Kehitysvaihtoehtoina vertaillaan johdon tien varteen siirtoa, maastokatkaisijoiden lisäämistä, pienitehoisten ja päättyvien haarajohtojen korvaamista 1 kV tekniikalla sekä pienoissähköaseman kannattavuutta. Työssä tarkastellaan yksityiskohtaisemmin Sodankylän käyttövarmuuden parantamista sähköasemavian aikana ja alueen kuormituksenkasvuun varautumista.

Performance Comparison of Behavioral Finance -based Investment Strategies in the Finnish Stock Market 1996-2010

In this thesis traditional investment strategies (value and growth) are compared to modern investment strategies (momentum, contrarian and GARP) in terms of risk, performance and cumulative returns. Strategies are compared during time period reaching from 1996 to 2010 in the Finnish stock market. Used data includes all listed main list stocks, dividends and is adjusted in case of splits, and mergers and acquisitions. Strategies are tested using different holding periods (6, 12 and 36 months) and data is divided into tercile portfolios based on different ranking criteria. Contrarian and growth strategies are the only strategies with improved cumulative returns when longer holding periods are used. Momentum (52-week high price1) and GARP strategies based on short holding period have the best performance and contrarian and growth strategies the worst. Momentum strategies (52-week high price) along with short holding period contrarian strategies (52-week low price2) have the lowest risk. Strategies with the highest risk are both growth strategies and two momentum strategies (52-week low price). The empirical results support the efficiency of momentum, GARP and value strategies. The least efficient strategies are contrarian and growth strategies in terms of risk, performance and cumulative returns. Most strategies outperform the market portfolio in all three measures. 1 Stock ranking criterion (current price/52-week highest price) 2 Stock ranking criterion (current price/52-week lowest price)

Assessing the Environmental Value of Water Treatment Solutions in the Mining Industry

Environmental accountability has become a major source of competitive advantage for industrial companies, because customers consider it as relevant buying criterion. However, in order to leverage their environmental responsibility, industrial suppliers have to be able to demonstrate the environmental value of their products and services, which is also the aim of Kemira, a global water chemistry company considered in this study. The aim of this thesis is to develop a tool which Kemira can use to assess the environmental value of their solutions for the customer companies in mining industry. This study answers to questions on what kinds of methods to assess environmental impacts exist, and what kind of tool could be used to assess the environmental value of Kemira’s water treatment solutions. The environmental impacts of mining activities vary greatly between different mines. Generally the major impacts include the water related issues and wastes. Energy consumption is also a significant environmental aspect. Water related issues include water consumption and impacts in water quality. There are several methods to assess environmental impacts, for example life cycle assessment, eco-efficiency tools, footprint calculations and process simulation. In addition the corresponding financial value may be estimated utilizing monetary assessment methods. Some of the industrial companies considered in the analysis of industry best practices use environmental and sustainability assessments. Based on the theoretical research and conducted interviews, an Excel based tool utilizing reference data on previous customer cases and customer specific test results was considered to be most suitable to assess the environmental value of Kemira’s solutions. The tool can be used to demonstrate the functionality of Kemira’s solutions in customers’ processes, their impacts in other process parameters and their environmental and financial aspects. In the future, the tool may be applied to fit also Kemira’s other segments, not only mining industry.