Ison tuuligeneraattorin roottorin ja staattorin rakennetarkastelu

Maailmanlaajuinen ilmastopolitiikka asettaa vaativia tavoitteita hiilidioksidipäästöjen vähentämiselle. Suurin haaste on tuottaa energiaa mahdollisimman alhaisin kustannuksin käyttäen uusiutuvia ja ympäristöä säästäviä energiamuotoja. Tuulivoimasta on tullut nopeimmin kehittyvä sähköntuotantotapa, ja tuuliturbiinien koon kasvun myötä on myös generaattorien koko kasvanut merkittävästi 1990-luvulta lähtien. Generaattorin massiivisuus suoravetoisessa tuuliturbiinin voimansiirrossa vaatii tarkkoja kuormitustarkasteluja, jotta rakenne kestäisi tuuliturbiinin eliniän. Tuuliturbiinin kuormitukset ovat stokastisia ja toisinaan erittäin suuria, mikä vaikeuttaa kuormitusten määrittämistä. Tuulen kuormitusten lisäksi generaattori altistuu eri toimintojen kautta muillekin kuormituksille, ja tästä syystä on otettava huomioon jarrutuksen, dynaamisen tasapainon ja ohjauksen sekä verkkovikojen aiheuttamat rasitukset tuuliturbiinin voimansiirrolle. Edellisten lisäksi työssä on tarkasteltu erilaisia rakenneratkaisuja sekä pyritty kiinnittämään huomio niiden kuormankantokykyyn ja jäykkyyteen sekä generaattorin keventämismahdollisuuksiin verrattuna perinteisiin radiaalivuogeneraattoreihin. Työssä on pyritty selvittämään rakenteen kuormitukset siten, että pystyttäisiin optimoimaan mahdollisimman kevyt rakenne. Optimoinnin kohteena on pinnarakenteisen generaattorin rakenteen massa puolien, puolan kulmien sekä tukirenkaan ja niistä aiheutuvien erilaisten rakenneyhdistelmien suhteen tarkasteltuna.

Demand forecasting process design and methods in medium sized enterprise

The purpose of this thesis was to study the design of demand forecasting processes and management of demand. In literature review were different processes found and forecasting methods and techniques interviewed. Also role of bullwhip effect in supply chain was identified and how to manage it with information sharing operations. In the empirical part of study is at first described current situation and challenges in case company. After that will new way to handle demand introduced with target budget creation and how information sharing with 5 products and a few customers would bring benefits to company. Also the new S&OP process created within this study and organization for it.

Low levels of sex hormone-binding globulin and hyperproinsulinemia as markers of increased pancreatic ß-cell demand in men

Low levels of sex hormone-binding globulin (SHBG) are considered to be an indirect index of hyperinsulinemia, predicting the later onset of diabetes mellitus type 2. In the insulin resistance state and in the presence of an increased pancreatic ß-cell demand (e.g. obesity) both absolute and relative increases in proinsulin secretion occur. In the present study we investigated the correlation between SHBG and pancreatic ß-cell secretion in men with different body compositions. Eighteen young men (30.0 ± 2.4 years) with normal glucose tolerance and body mass indexes (BMI) ranging from 22.6 to 43.2 kg/m2 were submitted to an oral glucose tolerance test (75 g) and baseline and 120-min blood samples were used to determine insulin, proinsulin and C-peptide by specific immunoassays. Baseline SHBG values were significantly correlated with baseline insulin (r = -0.58, P<0.05), proinsulin (r = -0.47, P<0.05), C-peptide (r = -0.55, P<0.05) and also with proinsulin at 120 min after glucose load (r = -0.58, P<0.05). Stepwise regression analysis revealed that proinsulin values at 120 min were the strongest predictor of SHBG (r = -0.58, P<0.05). When subjects were divided into obese (BMI >28 kg/m2, N = 8) and nonobese (BMI £25 kg/m2, N = 10) groups, significantly lower levels of SHBG were found in the obese subjects. The obese group had significantly higher baseline proinsulin, C-peptide and 120-min proinsulin and insulin levels. For the first time using a specific assay for insulin determination, a strong inverse correlation between insulinemia and SHBG levels was confirmed. The finding of a strong negative correlation between SHBG levels and pancreatic ß-cell secretion, mainly for the 120-min post-glucose load proinsulin levels, reinforces the concept that low SHBG levels are a suitable marker of increased pancreatic ß-cell demand.

The demand-supply balancing process in supply chain management - case mining & metals industry equipment

The aim of this thesis is to search how to match the demand and supply effectively in industrial and project-oriented business environment. The demand-supply balancing process is searched through three different phases: the demand planning and forecasting, synchronization of demand and supply and measurement of the results. The thesis contains a single case study that has been implemented in a company called Outotec. In the case study the demand is planned and forecasted with qualitative (judgmental) forecasting method. The quantitative forecasting methods are searched further to support the demand forecast and long term planning. The sales and operations planning process is used in the synchronization of the demand and supply. The demand forecast is applied in the management of a supply chain of critical unit of elemental analyzer. Different meters on operational and strategic level are proposed for the measurement of performance.

Utilization of AMI-Technology in a Multilayered Demand Response Service Environment

This thesis studied the performance of Advanced metering infrastructure systems in a challenging Demand Response environment. The aim was to find out what kind of challenges and bottlenecks could be met when utilizing AMI-systems in challenging Demand Response tasks. To find out the challenges and bottlenecks, a multilayered demand response service concept was formed. The service consists of seven different market layers which consist of Nordic electricity market and the reserve markets of Fingrid. In the simulations the AMI-systems were benchmarked against these seven market layers. It was found out, that the current generation AMI-systems were capable of delivering Demand Response on the most challenging market layers, when observed from time critical viewpoint. Additionally, it was found out, that to enable wide scale Demand Response there are three major challenges to be acknowledged. The challenges hindering the utilization of wide scale Demand Response were related to poor standardization of the systems in use, possible problems in data connectivity solutions and the current electricity market regulation model.

Accuracy improvement of a demand forecasting model

This research concerns different statistical methods that assist to increase the demand forecasting accuracy of company X’s forecasting model. Current forecasting process was analyzed in details. As a result, graphical scheme of logical algorithm was developed. Based on the analysis of the algorithm and forecasting errors, all the potential directions for model future improvements in context of its accuracy were gathered into the complete list. Three improvement directions were chosen for further practical research, on their basis, three test models were created and verified. Novelty of this work lies in the methodological approach of the original analysis of the model, which identified its critical points, as well as the uniqueness of the developed test models. Results of the study formed the basis of the grant of the Government of St. Petersburg.

Evaluating and improving demand forecast practices for B2B and B2C sectors

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. Former literature points out that even though many forecasting methods and approaches are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, it’s relatively rare that researches are focused on the differences in forecasting between consumer and industrial companies. The aim of this thesis is to investigate the potential of improving demand forecasting practices for B2B and B2C sectors in the global supply chains. Business to business (B2B) sector produces products for other manufacturing companies. On the other hand, consumer (B2C) sector provides goods for individual buyers. Usually industrial sector have a lower number of customers and closer relationships with them. The research questions of this thesis are: 1) What are the main differences and similarities in demand planning between B2B and B2C sectors? 2) How the forecast performance for industrial and consumer companies can be improved? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from a case company. Evaluation and improving in organizing demand forecasting can be found in three interlinked areas: 1) demand planning operational environment, 2) demand forecasting techniques, 3) demand information sharing scenarios. In this research current B2B and B2C demand practices are presented with further comparison between those two sectors. It was found that B2B and B2C sectors have significant differences in demand practices. This research partly filled the theoretical gap in understanding the difference in forecasting in consumer and industrial sectors. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Potential for synthetic gas in Finnish industry

Finland, other Nordic countries and European Union aim to decarbonize their energy production by 2050. Decarbonization requires large scale implementation of non-emission energy sources, i.e. renewable energy and nuclear power. Stochastic renewable energy sources present a challenge to balance the supply and demand for energy. Energy storages, non-emissions fuels in mobility and industrial processes are required whenever electrification is not possible. Neo-Carbon project studies the decarbonizing the energy production and the role of synthetic gas in it. This thesis studies the industrial processes in steel production, oil refining, cement manufacturing and glass manufacturing, where natural gas is already used or fuel switch to SNG is possible. The technical potential for fuel switching is assessed, and economic potential is necessary after this. All studied processes have potential for fuel switching, but total decarbonization of steel production, oil refining requires implementation of other zero-emission technologies.

Addressing conflicts of interest in the research paper: a societal demand in contemporary science?

In the last decade, dialogue between science and society has found a forum in an increasing number of publications on topics such as public engagement with science and public trust in science. Concerning the latter, issues that include cases of research misconduct, accountability in research, and conflicts of interest (COIs) have shaped global discussions on the communication of science. In the publication setting, the perception that hiding COIs and/or not managing them well may affect public trust in the research record has grown among editors. We conducted a search for editorials addressing COIs between 1989 and 2011, using four major databases: Medline/PubMed, Embase, Scopus, and Web of Knowledge. We explored the content of these editorials and the relationship they established between COIs and the public trust in science. Our results demonstrate that the relationship between disclosure of COIs and public trust in science has become a major concern among editors. We, thus, argue that COIs should be discussed more openly and frequently in graduate courses in the sciences, around the globe, not only in biomedical but also in non-biomedical areas. This is a critical issue in contemporary science, as graduate students are the future voices and decision-makers of the research community. Therefore, COIs, especially in the broader context of science and society, merit closer attention from policymakers, researchers, and educators. At times of great expectations for public engagement with science, mishandling of COIs may have undesirable consequences for public engagement with science and confidence in the scientific endeavor.

Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.