Open access and e-infrastructure

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Application of Carbon Nanotubes in Rotating Electrical Machines

Demand for increased energy efficiency has put an immense need for novel energy efficient systems. Electrical machines are considered as a much matured technology. Further improvement in this technology needs of finding new material to incorporate in electrical machines. Progress of carbon nanotubes research over the latest decade can open a new horizon in this aspect. Commonly known as ‘magic material’, carbon nanotubes (CNTs) have promising material properties that can change considerably the course of electrical machine design. It is believed that winding material based on carbon nanotubes create the biggest hope for a giant leap of modern technology and energy efficient systems. Though carbon nanotubes (CNTs) have shown amazing properties theoretically and practically during the latest 20 years, to the best knowledge of the author, no research has been carried out to find the future possibilities of utilizing carbon nanotubes as conductors in rotating electrical machines. In this thesis, the possibilities of utilizing carbon nanotubes in electrical machines have been studied. The design changes of electrical machine upon using carbon nanotubes instead of copper have been discussed vividly. A roadmap for this carbon nanotube winding machine has been discussed from synthesis, manufacturing and operational points of view.

Hedge-rahastojen menestyksen pysyvyys ja suhteellinen suoriutuminen sijoittajan näkökulmasta

The purpose of the thesis is to examine the long-term performance persistence and relative performance of hedge funds during bear and bull market periods. Performance metrics applied for fund rankings are raw return, Sharpe ratio, mean variance ratio and strategy distinctiveness index calculated of the original and clustered data correspondingly. Four different length combinations for selection and holding periods are employed. The persistence is examined using decile and quartile portfolio formatting approach and on the basis of Sharpe ratio and SKASR as performance metrics. The relative performance persistence is examined by comparing hedge portfolio returns during varying stock market conditions. The data is gathered from a private database covering 10,789 hedge funds and time horizon is set from January 1990 to December 2012. The results of this thesis suggest that long-term performance persistence of the hedge funds exists. The degree of persistence also depends on the performance metrics employed and length combination of selection and holding periods. The best results of performance persistence were obtained in the decile portfolio analysis on the basis of Sharpe ratio rankings for combination of 12-month selection period and the holding period of equal length. The results also suggest that the best performance persistence occurs in the Event Driven and Multi strategies. Dummy regression analysis shows that a relationship between hedge funds and stock market returns exists. Based on the results, Dedicated Short Bias, Global Macro, Managed Futures and Other strategies perform well during bear market periods. The results also indicate that the Market Neutral strategy is not absolutely market neutral and the Event Driven strategy has the best performance among all hedge strategies.

Planiglobii terrestris mappa universalis : utrumque hemisphaerium orient et occidentale repraesentans = Mappe-monde qui represente les deux hemisphères : savoir celui de l'orient et celui de l'occident

Irtokartta

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

Simulation of the Interaction Mean Free Path between Neutrons and TRISO Particles

The interaction mean free path between neutrons and TRISO particles is simulated using scripts written in MATLAB to solve the increasing error present with an increase in the packing factor in the reactor physics code Serpent. Their movement is tracked both in an unbounded and in a bounded space. Their track is calculated, depending on the program, linearly directly using the position vectors of the neutrons and the surface equations of all the fuel particles; by dividing the space in multiple subspaces, each of which contain a fraction of the total number of particles, and choosing the particles from those subspaces through which the neutron passes through; or by choosing the particles that lie within an infinite cylinder formed on the movement axis of the neutron. The estimate from the current analytical model, based on an exponential distribution, for the mean free path, utilized by Serpent, is used as a reference result. The results from the implicit model in Serpent imply a too long mean free path with high packing factors. The received results support this observation by producing, with a packing factor of 17 %, approximately 2.46 % shorter mean free path compared to the reference model. This is supported by the packing factor experienced by the neutron, the simulation of which resulted in a 17.29 % packing factor. It was also observed that the neutrons leaving from the surfaces of the fuel particles, in contrast to those starting inside the moderator, do not follow the exponential distribution. The current model, as it is, is thus not valid in the determination of the free path lengths of the neutrons.

Advanced analysis and design methods for preparative chromatographic separation processes

Preparative liquid chromatography is one of the most selective separation techniques in the fine chemical, pharmaceutical, and food industries. Several process concepts have been developed and applied for improving the performance of classical batch chromatography. The most powerful approaches include various single-column recycling schemes, counter-current and cross-current multi-column setups, and hybrid processes where chromatography is coupled with other unit operations such as crystallization, chemical reactor, and/or solvent removal unit. To fully utilize the potential of stand-alone and integrated chromatographic processes, efficient methods for selecting the best process alternative as well as optimal operating conditions are needed. In this thesis, a unified method is developed for analysis and design of the following singlecolumn fixed bed processes and corresponding cross-current schemes: (1) batch chromatography, (2) batch chromatography with an integrated solvent removal unit, (3) mixed-recycle steady state recycling chromatography (SSR), and (4) mixed-recycle steady state recycling chromatography with solvent removal from fresh feed, recycle fraction, or column feed (SSR–SR). The method is based on the equilibrium theory of chromatography with an assumption of negligible mass transfer resistance and axial dispersion. The design criteria are given in general, dimensionless form that is formally analogous to that applied widely in the so called triangle theory of counter-current multi-column chromatography. Analytical design equations are derived for binary systems that follow competitive Langmuir adsorption isotherm model. For this purpose, the existing analytic solution of the ideal model of chromatography for binary Langmuir mixtures is completed by deriving missing explicit equations for the height and location of the pure first component shock in the case of a small feed pulse. It is thus shown that the entire chromatographic cycle at the column outlet can be expressed in closed-form. The developed design method allows predicting the feasible range of operating parameters that lead to desired product purities. It can be applied for the calculation of first estimates of optimal operating conditions, the analysis of process robustness, and the early-stage evaluation of different process alternatives. The design method is utilized to analyse the possibility to enhance the performance of conventional SSR chromatography by integrating it with a solvent removal unit. It is shown that the amount of fresh feed processed during a chromatographic cycle and thus the productivity of SSR process can be improved by removing solvent. The maximum solvent removal capacity depends on the location of the solvent removal unit and the physical solvent removal constraints, such as solubility, viscosity, and/or osmotic pressure limits. Usually, the most flexible option is to remove solvent from the column feed. Applicability of the equilibrium design for real, non-ideal separation problems is evaluated by means of numerical simulations. Due to assumption of infinite column efficiency, the developed design method is most applicable for high performance systems where thermodynamic effects are predominant, while significant deviations are observed under highly non-ideal conditions. The findings based on the equilibrium theory are applied to develop a shortcut approach for the design of chromatographic separation processes under strongly non-ideal conditions with significant dispersive effects. The method is based on a simple procedure applied to a single conventional chromatogram. Applicability of the approach for the design of batch and counter-current simulated moving bed processes is evaluated with case studies. It is shown that the shortcut approach works the better the higher the column efficiency and the lower the purity constraints are.

Urvilja : när livet är människans hem

This caring science study explores ‘Will’ as an ontological concept. The aim is to deepen the understanding of the essence of Will, and to highlight the manifestations of Will and how Will becomes evident in clinical caring. Will is ontological and universal. Will is connected with the essence of the human being, and manifests in the human being as will. The approach is inspired by Gadamer’s philosophical hermeneutics. The study’s horizon of understanding consists of Eriksson’s caritative theory and the caring science-tradition. The study’s research questions are as follows: What is the essence of Will? What are its manifestations? How does Will become evident in clinical caring? The hermeneutic interpretative movement is initiated by the material, which consists of the philosopher Arthur Schopenhauer’s texts, letters from experts and dictionaries. Meaning-bearing substance fragments in the material are intertwined with the original horizon of understanding through hermeneutical reading, hermeneutical interpretation and concept analysis in an oscillating interpretive movement. An abstraction occurs when the new substance is illuminated by the caring science ontology. The oscillating interpretive movement results in a reinterpreted horizon of understanding, which in turn provides the findings of the study. The reinterpreted horizon of understanding is presented in the form of a theoretical model and abductive theses. The essence of Will is represented in the theoretical model as the lifeaffirming and the loving force. Life and love are Will’s origin and destination. Will’s manifestations (its diversity) hold conditions and chance occurrences that obstruct Will. Hence the will of the human being does not necessarily appear in a way that is in tune with ontological Will. Will represents the lifeblood of ethos, and in this lifeblood love flows. Will acts by virtue of itself, and gives ethos its force. Will manifests in a way that ethos can affirm. When Will is affected by caring its force is active in the service of life and love. Being a caregiver entails acting as a world-eye, which means recognizing Will in diversity. For caregivers, being a world-eye means observing fragments of Will as it manifests in its original form in the real reality, and acting as the mirror of life. The human being who is able to perceive the fundamental values of life and to live according to these has understood the laws of life and entered upon the human calling. The human being then lives according to the fundamental order and has found a home in life.

Predicting bankruptcy of Finnish limited liability companies from historical financial statements

This master’s thesis studies the probability of bankruptcy of Finnish limited liability companies as a part of credit risk assessment. The main idea of this thesis is to build and test bankruptcy prediction models for Finnish limited liability companies that can be utilized in credit decision making. The data used in this thesis consists of historical financial statements from 2112 Finnish limited liability companies, half of which have filed for bankruptcy. A total of four models are developed, two with logistic regression and two with multivariate discriminant analysis (MDA). The time horizon of the models varies from 1 to 2 years prior to the bankruptcy, and 14 different financial variables are used in the model formation. The results show that the prediction accuracy of the models ranges between 81.7% and 88.9%, and the best prediction accuracy is achieved with the one year prior the bankruptcy logistic regression model. However the difference between the best logistic model and the best MDA model is minimal. Overall based on the results of this thesis it can be concluded that predicting bankruptcy is possible to some extent, but naturally the results are not perfect.

Becoming a caring nurse : the heart of the matter in nurse education

This thesis in caring science didactics is based on a thinking, where the fundamental basis for the didactic is science-based, i.e. it does not emanate from the nursing profession but brings forward a didactic that grows out of caring science and its core substance and ethos. This view on didactics arises from the caritative theory developed by Eriksson. The overall aim of the study is to clarify the meaning and essence of understanding, as well as to explore and deepen the understanding of student nurses' processes of understanding and becoming with the intention of developing a theory model for caring didactics. The overarching research questions are: What is the essence of understanding (of caring science knowledge)? What are the possibilities and importance of understanding in the appropriation of caring science? What characterizes and impels the process of becoming? The thesis consists of four sub studies and a summary section. The overall methodological approach is hermeneutic involving quantitative as well as qualitative methods. The data for the study has been collected through a longitudinal research project that followed student nurses at three universities during their entire education. The empirical sub studies form the basis for the interpreted knowledge that is formulated in the new understanding. This new understanding have, through additional theory-charging with the theory fragments from Gadamer, generated the heuristic synthesis which is illustrated in the theory model. The findings shows that understanding can be described as something unlimited, as an endless movement, which can be illustrated as a lying eighth, a lemniscate. The lemiscate of understanding is characterized by seeing, knowing and becoming and consists of seven differently named phases; the acquired horizon of understanding, the encounter of horizons, the dialogue of horizons, the fusion of horizons, application, reflection and shaping a new horizon of understanding. Bildung (formation), is the ultimate imprint of the endless spiral movement of understanding. Ethos and arête constitute the hubs around which the lemniscate of understanding circles. These include the spirit and driving force that the student carries within. The caring culture encloses the lemniscate of understanding. The caring culture provides the life space of understanding and the prevailing basic values are evinced in the culture.

Genetically Modified Organisms (GMOs) and Agroecology in Agricultural Production in the United States - A Comparative Analysis.

The world’s population is growing at a rapid rate and one of the primary problems of a growing is food supply. To ensure food supply and security, the biggest companies in the agricultural sector of the United States and all over the world have collaborated to produce genetically modified organisms, including crops, that have a tendency to increase yields and are speculated to reduce pesticide use. It’s a technology that is declared to have a multitude of benefits. During the same time period another set of practices has risen to the horizon by the name of agroecology. It spreads across many different sectors such as politics, sociology, environment, health and so on. Moreover, it involves primitive organic techniques that can be applied at farm level to enhance the performance of an ecosystem to effectively decrease the negative effect on environment and health of individuals while producing good quality foods. Since both the processes proclaim sustainable development, a natural question may come in mind that which one seems more favorable? During the course of this study, genetically modified organisms (GMOs) and agroecology are compared within the sphere of social, environmental and health aspects. The results derived upon a comparative analysis of scientific literature tend to prove that GMOs pose a greater threat to the environment, health of individuals and the generalized social balance in the United States compared to agroecological practices. Economic indicators were not included in the study and more studies might be needed in the future to get a broader view on the subject.

Planiglobii Terrestris mappa vniversalis, utrumq[ue] Hemisphaerium Orient et Occidentale repraesentans ex. IV. mappis generalibus Hasianis composita et adjectis ceteris hemisphaeriis designata a G. M. Lowizio.

Pallonpuoliskot halkaisijaltaan n. 26 cm.

Aircraft tracking and classification with vhf passive bistatic radar

Since the times preceding the Second World War the subject of aircraft tracking has been a core interest to both military and non-military aviation. During subsequent years both technology and configuration of the radars allowed the users to deploy it in numerous fields, such as over-the-horizon radar, ballistic missile early warning systems or forward scatter fences. The latter one was arranged in a bistatic configuration. The bistatic radar has continuously re-emerged over the last eighty years for its intriguing capabilities and challenging configuration and formulation. The bistatic radar arrangement is used as the basis of all the analyzes presented in this work. The aircraft tracking method of VHF Doppler-only information, developed in the first part of this study, is solely based on Doppler frequency readings in relation to time instances of their appearance. The corresponding inverse problem is solved by utilising a multistatic radar scenario with two receivers and one transmitter and using their frequency readings as a base for aircraft trajectory estimation. The quality of the resulting trajectory is then compared with ground-truth information based on ADS-B data. The second part of the study deals with the developement of a method for instantaneous Doppler curve extraction from within a VHF time-frequency representation of the transmitted signal, with a three receivers and one transmitter configuration, based on a priori knowledge of the probability density function of the first order derivative of the Doppler shift, and on a system of blocks for identifying, classifying and predicting the Doppler signal. The extraction capabilities of this set-up are tested with a recorded TV signal and simulated synthetic spectrograms. Further analyzes are devoted to more comprehensive testing of the capabilities of the extraction method. Besides testing the method, the classification of aircraft is performed on the extracted Bistatic Radar Cross Section profiles and the correlation between them for different types of aircraft. In order to properly estimate the profiles, the ADS-B aircraft location information is adjusted based on extracted Doppler frequency and then used for Bistatic Radar Cross Section estimation. The classification is based on seven types of aircraft grouped by their size into three classes.

Defining Sales and Operations Planning Process in an Environmental Management Company

Sales and operations research publications have increased significantly in the last decades. The concept of sales and operations planning (S&OP) has gained increased recognition and has been put forward as the area within Supply Chain Management (SCM). Development of S&OP is based on the need for determining future actions, both for sales and operations, since off-shoring, outsourcing, complex supply chains and extended lead times make challenges for responding to changes in the marketplace when they occur. Order intake of the case company has grown rapidly during the last years. Along with the growth, new challenges considering data management and information flow have arisen due to increasing customer orders. To manage these challenges, case company has implemented S&OP process, though initial process is in early stage and due to this, the process is not managing the increased customer orders adequately. Thesis objective is to explore extensively the S&OP process content of the case company and give further recommendations. Objectives are categorized into six different groups, to clarify the purpose of this thesis. Qualitative research methods used are active participant observation, qualitative interviews, enquiry, education, and a workshop. It is notable that demand planning was felt as cumbersome, so it is typically the biggest challenge in S&OP process. More proactive the sales forecasting can be, more expanded the time horizon of operational planning will turn out. S&OP process is 60 percent change management, 30 percent process development and 10 percent technology. The change management and continuous improvement can sometimes be arduous and set as secondary. It is important that different people are required to improve the process and the process is constantly evaluated. As well as, process governance is substantially in a central role and it has to be managed consciously. Generally, S&OP process was seen important and all the stakeholders were committed to the process. Particular sections were experienced more important than others, depending on the stakeholders’ point of views. Recommendations to objective groups are evaluated by the achievable benefit and resource requirement. The urgent and easily implemented improvement recommendations should be executed firstly. Next steps are to develop more coherent process structure and refine cost awareness. Afterwards demand planning, supply planning, and reporting should be developed more profoundly. For last, information technology system should be implemented to support the process phases.

A Bayesian Approach for Forecasting Heat Load in a District Heating System

The growing population in cities increases the energy demand and affects the environment by increasing carbon emissions. Information and communications technology solutions which enable energy optimization are needed to address this growing energy demand in cities and to reduce carbon emissions. District heating systems optimize the energy production by reusing waste energy with combined heat and power plants. Forecasting the heat load demand in residential buildings assists in optimizing energy production and consumption in a district heating system. However, the presence of a large number of factors such as weather forecast, district heating operational parameters and user behavioural parameters, make heat load forecasting a challenging task. This thesis proposes a probabilistic machine learning model using a Naive Bayes classifier, to forecast the hourly heat load demand for three residential buildings in the city of Skellefteå, Sweden over a period of winter and spring seasons. The district heating data collected from the sensors equipped at the residential buildings in Skellefteå, is utilized to build the Bayesian network to forecast the heat load demand for horizons of 1, 2, 3, 6 and 24 hours. The proposed model is validated by using four cases to study the influence of various parameters on the heat load forecast by carrying out trace driven analysis in Weka and GeNIe. Results show that current heat load consumption and outdoor temperature forecast are the two parameters with most influence on the heat load forecast. The proposed model achieves average accuracies of 81.23 % and 76.74 % for a forecast horizon of 1 hour in the three buildings for winter and spring seasons respectively. The model also achieves an average accuracy of 77.97 % for three buildings across both seasons for the forecast horizon of 1 hour by utilizing only 10 % of the training data. The results indicate that even a simple model like Naive Bayes classifier can forecast the heat load demand by utilizing less training data.