Influence of duty factor on the die-sinking Electrical Discharge Machining of high-strength aluminum alloy under rough machining

The use of high-strength aluminium alloys as material for injection molding tools to produce small and medium batches of plastic products as well as prototyping molds is becoming of increasing demand by the tooling industry. These alloys are replacing the traditional use of steel in the cases above because they offer many advantages such as very high thermal conductivity associated with good corrosion and wear resistance presenting good machinability in milling and electrical discharge machining operations. Unfortunately there is little technological knowledge on the Electrical Discharge Machining (EDM) of high-strength aluminium alloys, especially about the AMP 8000 alloy. The duty factor, which means the ratio between pulse duration and pulse cycle time exerts an important role on the performance of EDM. This work has carried out an experimental study on the variation of the duty factor in order to analyze its influence on material removal rate and volumetric relative wear under roughing conditions of EDM process. The results showed that high values of duty factor are possible to be applied without bringing instability into the EDM process and with improvement of material removal rate and volumetric relative wear.

Testing and simulation of fractionary electromechanical rotative drives

This paper concerns the development of drives that use electromechanical rotative motor systems. It is proposed an experimental drive test structure integrated to simulation softwares. The objective of this work is to show that an affordable model validation procedure can be obtained by combining a precision data acquisition with well tuned state-of-the-art simulation packages. This is required for fitting, in the best way, a drive to its load or, inversely, to adapt loads to given drive characteristics.

Price spike forecasting in a competitive day-ahead energy market

Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

Long-term nutrient load management and lake restoration: Case of Säkylän Pyhäjärvi (SW Finland)

Eutrophication caused by anthropogenic nutrient pollution has become one of the most severe threats to water bodies. Nutrients enter water bodies from atmospheric precipitation, industrial and domestic wastewaters and surface runoff from agricultural and forest areas. As point pollution has been significantly reduced in developed countries in recent decades, agricultural non-point sources have been increasingly identified as the largest source of nutrient loading in water bodies. In this study, Lake Säkylän Pyhäjärvi and its catchment are studied as an example of a long-term, voluntary-based, co-operative model of lake and catchment management. Lake Pyhäjärvi is located in the centre of an intensive agricultural area in southwestern Finland. More than 20 professional fishermen operate in the lake area, and the lake is used as a drinking water source and for various recreational activities. Lake Pyhäjärvi is a good example of a large and shallow lake that suffers from eutrophication and is subject to measures to improve this undesired state under changing conditions. Climate change is one of the most important challenges faced by Lake Pyhäjärvi and other water bodies. The results show that climatic variation affects the amounts of runoff and nutrient loading and their timing during the year. The findings from the study area concerning warm winters and their influences on nutrient loading are in accordance with the IPCC scenarios of future climate change. In addition to nutrient reduction measures, the restoration of food chains (biomanipulation) is a key method in water quality management. The food-web structure in Lake Pyhäjärvi has, however, become disturbed due to mild winters, short ice cover and low fish catch. Ice cover that enables winter seining is extremely important to the water quality and ecosystem of Lake Pyhäjärvi, as the vendace stock is one of the key factors affecting the food web and the state of the lake. New methods for the reduction of nutrient loading and the treatment of runoff waters from agriculture, such as sand filters, were tested in field conditions. The results confirm that the filter technique is an applicable method for nutrient reduction, but further development is needed. The ability of sand filters to absorb nutrients can be improved with nutrient binding compounds, such as lime. Long-term hydrological, chemical and biological research and monitoring data on Lake Pyhäjärvi and its catchment provide a basis for water protection measures and improve our understanding of the complicated physical, chemical and biological interactions between the terrestrial and aquatic realms. In addition to measurements carried out in field conditions, Lake Pyhäjärvi and its catchment were studied using various modelling methods. In the calibration and validation of models, long-term and wide-ranging time series data proved to be valuable. Collaboration between researchers, modellers and local water managers further improves the reliability and usefulness of models. Lake Pyhäjärvi and its catchment can also be regarded as a good research laboratory from the point of view of the Baltic Sea. The main problem in both of them is eutrophication caused by excess nutrients, and nutrient loading has to be reduced – especially from agriculture. Mitigation measures are also similar in both cases.

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.

Forecasting of wind speeds and directions with artificial neural networks

In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.

Electrical status epilepticus during sleep. Continuous spikes and waves during sleep

ABSTRACT Maria Peltola Electrical status epilepticus during sleep – Continuous spikes and waves during sleep Department of Clinical Neurophysiology, University of Turku Department of Clinical Neurophysiology and Department of Pediatric Neurology, Children’s Hospital, Helsinki University Central Hospital Annales Universitatis Turkuensis, Medica-Odontologica, Turku, Finland, 2014 Background: Electrical status epilepticus during sleep (ESES) is an EEG phenomenon of frequent spikes and waves occurring in slow sleep. ESES relates to cognitive deterioration in heterogeneous childhood epilepsies. Validated methods to quantitate ESES are missing. The clinical syndrome, called epileptic encephalopathy with continuous spikes and waves during sleep (CSWS) is pharmacoresistant in half of the patients. Limited data exists on surgical treatment of CSWS. Aims and methods: The effects of surgical treatment were studied by investigating electroclinical outcomes in 13 operated patients (nine callosotomies, four resections) with pharmacoresistant CSWS and cognitive decline. Secondly, an objective paradigm was searched for assessing ESES by the semiautomatic quantification of spike index (SI) and measuring spike strength from EEG. Results: Postoperatively, cognitive deterioration was stopped in 12 (92%) patients. Three out of four patients became seizure-free after resective surgery. Callosotomy resulted in greater than 90% reduction of atypical absences in six out of eight patients. The preoperative propagation of ESES from one hemisphere to the other was associated with a good response. Semiautomatic quantification of SI was a robust method when the maximal interspike interval of three seconds was used to determine the “continuous” discharge in ten EEGs. SI of the first hour of sleep appeared representative of the whole night SI. Furthermore, the spikes’ root mean square was found to be a stable measure of spike strength when spatially integrated over multiple electrodes during steady NREM sleep. Conclusions: Patients with pharmacoresistant CSWS, based on structural etiology, may benefit from resective surgery or corpus callosotomy regarding both seizure outcome and cognitive prognosis. The semiautomated SI quantification, with proper userdefined settings and the new spatially integrated measure of spike strength, are robust and promising tools for quantifying ESES. Keywords: Electrical status epilepticus during sleep, ESES, continuous spikes and waves during sleep, CSWS, epilepsy surgery, spike index, spike strength, RMS TIIVISTELMÄ Maria Peltola Unenaikainen sähköinen status epilepticus Kliininen neurofysiologia, Turun yliopisto Kliininen neurofysiologia ja lastenneurologia, Lasten ja nuorten sairaala, Helsingin yliopistollinen keskussairaala Annales Universitatis Turkuensis, Medica-Odontologica, Turku, Suomi, 2014 Tausta: Sähköinen status epilepticus unessa (ESES) on aivosähkökäyrä (EEG)-ilmiö, jossa hidasaaltounen aikana esiintyy tiheä piikkihidasaaltopurkaus. ESES:n kvantifioimiseen ei ole olemassa validoituja menetelmiä. ESES on liitetty kognitiivisen tason laskuun ja tällöin puhutaan CSWS (continuous spikes and waves during sleep) - oireyhtymästä. CSWS ei vastaa lääkehoitoon puolella potilaista ja sen epilepsiakirurgisesta hoidosta on olemassa vain vähän tietoa. Tavoitteet ja menetelmät: Selvitimme retrospektiivisesti epilepsiakirurgian vaikusta elektrokliinisiin löydöksiin 13:lla lääkeresistenttiä CSWS-oireyhtymää sairastavalla lapsella, joilla oli rakenteellinen aivojen poikkeavuus. Toinen tavoite oli löytää objektiivinen puoliautomaattinen tapa mitata purkauksen määrää ja piikkien voimakkuutta EEG:stä. Tulokset: Kognitiivisen tason jatkuva heikentyminen loppui 12 (92 %) potilaalla leikkauksen jälkeen. Kolme neljästä resektiopotilaasta tuli kohtauksettomaksi. Kallosotomian jälkeen kuudella kahdeksasta potilaasta päivittäiset kohtaukset vähenivät yli 90 %:lla. Purkauksen leviäminen leikkausta edeltävästi vain yhdestä hemisfääristä toiseen liittyi hyvään leikkaushoitovasteeseen. Piikki-indeksi, jossa käytetään jatkuvan purkauksen määritelmänä maksimissaan kolmea sekuntia piikkien välillä, osoittautui luotettavaksi menetelmäksi ESES:n kvantifioimiseen. Useammasta elektrodista integroitu piikkien neliöllinen keskiarvo oli piikin voimakkuuden vakaa mitta häiriintymättömässä NREM-unessa. Päätelmät: Lääkehoidolle vastaamatonta CSWS:ää sairastavat potilaat, joilla on rakenteellinen aivopoikkeavuus ja yhdensuuntainen purkauksen leviämismalli, näyttävät kohtausten vähenemisen lisäksi hyötyvän epilepsiakirurgiasta kognitiivisesti. Puoliautomaattinen piikki-indeksin kvantifiointi sopivilla käyttäjäasetuksilla ja uusi spatiaalisesti integroitu piikin voimakkuuden mittari ovat stabiileja ja lupaavia ESES:n kvantitatiivisia mittareita. Avainsanat: Unenaikainen sähköinen status epilepticus, ESES, CSWS, epilepsiakirurgia, piikki-indeksi, piikin voimakkuus, neliöllinen keskiarvo

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.

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.

Signaled two-way avoidance learning using electrical stimulation of the inferior colliculus as negative reinforcement: effects of visual and auditory cues as warning stimuli

The inferior colliculus is a primary relay for the processing of auditory information in the brainstem. The inferior colliculus is also part of the so-called brain aversion system as animals learn to switch off the electrical stimulation of this structure. The purpose of the present study was to determine whether associative learning occurs between aversion induced by electrical stimulation of the inferior colliculus and visual and auditory warning stimuli. Rats implanted with electrodes into the central nucleus of the inferior colliculus were placed inside an open-field and thresholds for the escape response to electrical stimulation of the inferior colliculus were determined. The rats were then placed inside a shuttle-box and submitted to a two-way avoidance paradigm. Electrical stimulation of the inferior colliculus at the escape threshold (98.12 ± 6.15 (A, peak-to-peak) was used as negative reinforcement and light or tone as the warning stimulus. Each session consisted of 50 trials and was divided into two segments of 25 trials in order to determine the learning rate of the animals during the sessions. The rats learned to avoid the inferior colliculus stimulation when light was used as the warning stimulus (13.25 ± 0.60 s and 8.63 ± 0.93 s for latencies and 12.5 ± 2.04 and 19.62 ± 1.65 for frequencies in the first and second halves of the sessions, respectively, P<0.01 in both cases). No significant changes in latencies (14.75 ± 1.63 and 12.75 ± 1.44 s) or frequencies of responses (8.75 ± 1.20 and 11.25 ± 1.13) were seen when tone was used as the warning stimulus (P>0.05 in both cases). Taken together, the present results suggest that rats learn to avoid the inferior colliculus stimulation when light is used as the warning stimulus. However, this learning process does not occur when the neutral stimulus used is an acoustic one. Electrical stimulation of the inferior colliculus may disturb the signal transmission of the stimulus to be conditioned from the inferior colliculus to higher brain structures such as amygdala

Monitoring human cytomegalovirus viral load in peripheral blood leukocytes of renal transplant recipients by a simple limiting dilution-PCR assay

To assess the clinical relevance of a semi-quantitative measurement of human cytomegalovirus (HCMV) DNA in renal transplant recipients within the typical clinical context of a developing country where virtually 100% of both receptors and donors are seropositive for this virus, we have undertaken HCMV DNA quantification using a simple, semi-quantitative, limiting dilution polymerase chain reaction (PCR). We evaluated this assay prospectively in 52 renal transplant patients from whom a total of 495 serial blood samples were collected. The samples scored HCMV positive by qualitative PCR had the levels of HCMV DNA determined by end-point dilution-PCR. All patients were HCMV DNA positive during the monitoring period and a diagnosis of symptomatic infection was made for 4 of 52 patients. In symptomatic patients the geometric mean of the highest level of HCMV DNAemia was 152,000 copies per 106 leukocytes, while for the asymptomatic group this value was 12,050. Symptomatic patients showed high, protracted HCMV DNA levels, whereas asymptomatic patients demonstrated intermittent low or moderate levels. Using a cut-off value of 100,000 copies per 106 leukocytes, the limiting dilution assay had sensitivity of 100%, specificity of 92%, a positive predictive value of 43% and a negative predictive value of 100% for HCMV disease. In this patient group, there was universal HCMV infection but relatively infrequent symptomatic HCMV disease. The two patient groups were readily distinguished by monitoring with the limiting dilution assay, an extremely simple technology immediately applicable in any clinical laboratory with PCR capability.

Regulation of intercellular coupling in acute and chronic heart disease

Effective pump function of the heart depends on the precise control of spatial and temporal patterns of electrical activation. Accordingly, the distribution and function of gap junction channels are important determinants of the conduction properties of myocardium and undoubtedly play other roles in intercellular communication crucial to normal cardiac function. Recent advances have begun to elucidate mechanisms by which the heart regulates intercellular electrical coupling at gap junctions in response to stress or injury. Although responses to increased load or injury are generally adaptive in nature, remodeling of intercellular junctions under conditions of severe stress creates anatomic substrates conducive to the development of lethal ventricular arrhythmias. Potential mechanisms controlling the level of intercellular communication in the heart include regulation of connexin turnover dynamics and phosphorylation.

The Impact of Electrical Capacity Market Mechanisms on Capacity Mobility and End Use Customer Pricing

Potential impacts of electrical capacity market design on capacity mobility and end use customer pricing are analyzed. Market rules and historical evolution are summarized to provide a background for the analysis. The summarized rules are then examined for impacts on capacity mobility. A summary of the aspects of successful capacity markets is provided. Two United States market regions are chosen for analysis based upon their market history and proximity to each other. The MISO region is chosen due to recent developments in capacity market mechanisms. The PJM region neighbors the MISO region and is similar in size and makeup. The PJM region has had a capacity market mechanism for over a decade and allows for a controlled comparison of the MISO region’s developments. Capacity rules are found to have an impact on the mobility of capacity between regions. Regulatory restrictions and financial penalties for the movement of capacity between regions are found which effectively hinder such mobility. Capacity market evolution timelines are formed from the historical evolution previously summarized and compared to historical pricing to inspect for a correlation. No direct and immediate impact on end use customer pricing was found due to capacity market design. The components of end use customer pricing are briefly examined.

Forecasting financial weather - can we foresee market sentiment? Spectrum of stock price behavior - NYSE case study

The desire to create a statistical or mathematical model, which would allow predicting the future changes in stock prices, was born many years ago. Economists and mathematicians are trying to solve this task by applying statistical analysis and physical laws, but there are still no satisfactory results. The main reason for this is that a stock exchange is a non-stationary, unstable and complex system, which is influenced by many factors. In this thesis the New York Stock Exchange was considered as the system to be explored. A topological analysis, basic statistical tools and singular value decomposition were conducted for understanding the behavior of the market. Two methods for normalization of initial daily closure prices by Dow Jones and S&P500 were introduced and applied for further analysis. As a result, some unexpected features were identified, such as a shape of distribution of correlation matrix, a bulk of which is shifted to the right hand side with respect to zero. Also non-ergodicity of NYSE was confirmed graphically. It was shown, that singular vectors differ from each other by a constant factor. There are for certain results no clear conclusions from this work, but it creates a good basis for the further analysis of market topology.

Forecasting financial weather - can we foresee market sentiment? Quantitative analysis of nodal prices in the New Zealand Electricity Spot Market

Time series of hourly electricity spot prices have peculiar properties. Electricity is by its nature difficult to store and has to be available on demand. There are many reasons for wanting to understand correlations in price movements, e.g. risk management purposes. The entire analysis carried out in this thesis has been applied to the New Zealand nodal electricity prices: offer prices (from 29 May 2002 to 31 March 2009) and final prices (from 1 January 1999 to 31 March 2009). In this paper, such natural factors as location of the node and generation type in the node that effects the correlation between nodal prices have been reviewed. It was noticed that the geographical factor affects the correlation between nodes more than others. Therefore, the visualisation of correlated nodes was done. However, for the offer prices the clear separation of correlated and not correlated nodes was not obtained. Finally, it was concluded that location factor most strongly affects correlation of electricity nodal prices; problems in visualisation probably associated with power losses when the power is transmitted over long distance.