18 resultados para CPU load

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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In this final project the high availability options for PostgreSQL database management system were explored and evaluated. The primary objective of the project was to find a reliable replication system and implement it to a production environment. The secondary objective was to explore different load balancing methods and compare their performance. The potential replication methods were thoroughly examined, and the most promising was implemented to a database system gathering weather information in Lithuania. The different load balancing methods were tested performance wise with different load scenarios and the results were analysed. As a result for this project a functioning PostgreSQL database replication system was built to the Lithuanian Hydrometeorological Service's headquarters, and definite guidelines for future load balancing needs were produced. This study includes the actual implementation of a replication system to a demanding production environment, but only guidelines for building a load balancing system to the same production environment.

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Abstract

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On yleisesti tiedossa, että väsyttävän kuormituksen alaisena olevat hitsatut rakenteet rikkoutuvat juuri hitsausliitoksista. Täyden tunkeuman hitsausliitoksia sisältävien rakenteiden asiantunteva suunnittelu janykyaikaiset valmistusmenetelmät ovat lähes eliminoineet väsymisvauriot hitsatuissa rakenteissa. Väsymislujuuden parantaminen tiukalla täyden tunkeuman vaatimuksella on kuitenkin epätaloudellinen ratkaisu. Täyden tunkeuman hitsausliitoksille asetettavien laatuvaatimuksien on määriteltävä selkeät tarkastusohjeet ja hylkäämisperusteet. Tämän diplomityön tarkoituksena oli tutkia geometristen muuttujien vaikutusta kuormaa kantavien hitsausliitosten väsymislujuuteen. Huomio kiinnitettiin pääasiassa suunnittelumuuttujiin, joilla on vaikutusta väsymisvaurioiden syntymiseen hitsauksen juuren puolella. Nykyiset määräykset ja standardit, jotka perustuvat kokeellisiin tuloksiin; antavat melko yleisiä ohjeita hitsausliitosten väsymismitoituksesta. Tämän vuoksi muodostettiin kokonaan uudet parametriset yhtälöt sallitun nimellisen jännityksen kynnysarvon vaihteluvälin, ¿¿th, laskemiseksi, jotta vältettäisiin hitsausliitosten juuren puoleiset väsymisvauriot. Lisäksi, jokaiselle liitostyypille laskettiin hitsin juuren puolen väsymisluokat (FAT), joita verrattiin olemassa olevilla mitoitusohjeilla saavutettuihin tuloksiin. Täydentäviksi referensseiksi suoritettiin useita kolmiulotteisia (3D) analyysejä. Julkaistuja kokeellisiin tuloksiin perustuvia tietoja käytettiin apuna hitsausliitosten väsymiskäyttäytymisen ymmärtämiseksi ja materiaalivakioiden määrittämiseksi. Kuormaa kantavien vajaatunkeumaisten hitsausliitosten väsymislujuus määritettiin käyttämällä elementtimenetelmää. Suurimman pääjännityksen kriteeriä hyödynnettiin murtumiskäyttäytymisen ennakoimiseksi. Valitulle hitsatulle materiaalille ja koeolosuhteille murtumiskäyttäytymistä mallinnettiin särön kasvunopeudella da/dN ja jännitysintensiteettikertoimen vaihteluvälillä, 'K. Paris:n yhtälön numeerinen integrointi suoritettiin FRANC2D/L tietokoneohjelmalla. Saatujen tulosten perusteella voidaan laskea FAT tutkittavassa tapauksessa. ¿¿th laskettiin alkusärön jännitysintensiteettikertoimen vaihteluvälin ja kynnysjännitysintensiteettikertoimen, 'Kth, perusteella. ¿Kth arvoa pienemmällä vaihteluvälillä särö ei kasva. Analyyseissäoletuksena oli hitsattu jälkikäsittelemätön liitos, jossa oli valmis alkusärö hitsin juuressa. Analyysien tulokset ovat hyödyllisiä suunnittelijoille, jotka tekevät päätöksiä koskien geometrisiä parametreja, joilla on vaikutusta hitsausliitosten väsymislujuuteen.

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The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.

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A variable temperature field sets exacting demands to the structure under mechanical load. Most of all the lifetime of the rotating drum structure depends on temperature differences between parts inside the drum. The temperature difference was known because of the measurements made before. The list of demands was created based on customers’ needs. The limits of this paper were set to the inner structure of the drum. Creation of ideas for the inner structure was started open minded. The main principle in the creation process was to create new ideas for the function of the product with the help of sub-functions. The sub-functions were created as independent as possible. The best sub-functions were combined together and the new working principles were created based on them. Every working principle was calculated separately and criticized at the end of the calculation process. The main objective was to create the new kind of structure, which is not based too much to the old, inoperative structure. The affect of own weight of the inner structure to the stress values was quite small but it was also taken into consideration when calculating the maximum stress value of the structure. Because of very complex structures all of the calculations were made with the help of the ProE – Mechanica software. The fatigue analyze was made also for the best structure solution.

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Työn tarkoituksena oli analysoida polttoainesauvojen käyttäytymistä Loviisan ydinvoimalaitoksen tehonsäätöajossa. Sähkömarkkinoiden vapautuminen Pohjoismaissa sekä tämän seurauksena vaihteleva sähkön markkinahinta ovat ajaneet sähkötuottajat tilanteeseen, jossa tuotanto aiempaa enemmän mukautuu markkinatilanteeseen. Näin ollen myös Loviisan ydinvoimalaitoksen osallistuminen sähkön tuotannon säätelyyn saattaa tulevaisuudessa olla ajankohtaista. Ennen kuin reaktorin tehonsäätöajoa voidaan alkaa toteuttaa, tulee varmistua siitä, että polttoainesauvassa tehonsäätöjen seurauksena tapahtuvat muutokset eivät aiheuta epäsuotuisia käyttäytymisilmiöitä. Työssä tarkastellaan kahden Loviisan ydinvoimalaitoksen polttoainetoimittajan, British Nuclear Fuels plc:n ja venäläisen TVEL:n ensinippujen polttoainesauvan käyttäytymistä tehonsäätötapauksissa. Työssä tarkastellut tehonsäätötapaukset on pyritty valitsemaan niin, että ne kuvaisivat tulevaisuudessa mahdollisesti toteutettavia tehonsäätöjä. Laskentatapauksien sauvatehohistoriat on generoitu HEXBU-3D sydänsimulaattoriohjelmalla lasketun nelivuotisen perustehohistorian pohjalta lisäämällä säätösauvan aiheuttama reaktoritehon muutos, säätösauvan viereisen polttoainenipun aksiaalitehon muutos sekä säätösauvan rakenteen aiheuttama paikallinen tehopiikki säätösauvan vieressä. Työssä tarkastellaan tehonsäätöjen toteuttamista eri tehotasoille ja vaihtelevilla määrillä tehonsäätösyklejä. Työssä käsitellyt laskentatapaukset on jaoteltu reaktorin ajotavan mukaan seuraavasti: peruskuorma-ajo, viikonloppusäätö ja päiväsäätö. Laskenta suoritettiin ydinpolttoaineen käyttäytymistä kuvaavaa ENIGMA-B 7.3.0 ohjelmaa apuna käyttäen. Laskelmien tulokset osoittavat, että molempien polttoainetoimittajien ensinippujen sauvat kestävät reaktorin tehonsäätöajoa rajoituksetta tarkastelluissa laskentatapauksissa. ENIGMA-ohjelman sisältämät mallit, jotka ennustavat polttoainesauvan suojakuoren vaurioitumistodennäköisyyden jännityskorroosion tai väsymismurtuman kautta, eivät näytä mitään merkkejä vaurioitumisesta. BNFL:n polttoainesauva saavuttaa kuitenkin suurempia väsymismurtumatodennäköisyyden arvoja. Tämä johtuu siitä, että polttoainepelletin ja suojakuoren välinen mekaaninen vuorovaikutus syntyy BNFL:n sauvassa aikaisemmin, joka taas johtaa suurempaan määrään sauvaa rasittavia muodonmuutoksia tehonnostotilanteissa. TVEL:n Zr1%Nb -materiaalista valmistetun suojakuoren käyttäytymistä ei voida kuitenkaan suoraan näiden laskujen perusteella arvioida, sillä ENIGMA-ohjelman mallit perustuvat Zircaloy-suojakuorimateriaaleilla suoritettuihin kokeisiin.

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Suorituskyky- ja kuormitustestien tekeminen sovelluksille on erittäin tärkeä osa tuotantoprosessia nykypäivänä. Myös Web-sovelluksia testataan yhä enemmän. Tarve suorituskyky- ja kuormitustestien tekemiselle on selvä. Testattavan ympäristön tämänhetkinen, mutta myös tulevaisuuden toimivuus taataan oikein tehdyillä testeillä ja niitä seuraavilla korjaustoimenpiteillä. Suurten käyttäjämäärien testaaminen manuaalisesti on kuitenkin hyvin vaikeaa. Sirpaleisen ympäristön, kuten palveluihin perustuvien Web-sovellusympäristöjen testaaminen on haaste. Tämän työn aiheena on arvioida työkaluja ja menetelmiä, joilla raskaita teollisia Web-sovelluksia voidaan testata. Tavoitteena on löytää testausmenetelmiä, joilla voidaan luotettavasti simuloida suuria käyttäjämääriä. Tavoitteena on myös arvioida erilaisten yhteyksien ja protokollien vaikutusta Web-sovelluksen suorituskykyyn.

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Industry's growing need for higher productivity is placing new demands on mechanisms connected with electrical motors, because these can easily lead to vibration problems due to fast dynamics. Furthermore, the nonlinear effects caused by a motor frequently reduce servo stability, which diminishes the controller's ability to predict and maintain speed. Hence, the flexibility of a mechanism and its control has become an important area of research. The basic approach in control system engineering is to assume that the mechanism connected to a motor is rigid, so that vibrations in the tool mechanism, reel, gripper or any apparatus connected to the motor are not taken into account. This might reduce the ability of the machine system to carry out its assignment and shorten the lifetime of the equipment. Nonetheless, it is usually more important to know how the mechanism, or in other words the load on the motor, behaves. A nonlinear load control method for a permanent magnet linear synchronous motor is developed and implemented in the thesis. The purpose of the controller is to track a flexible load to the desired velocity reference as fast as possible and without awkward oscillations. The control method is based on an adaptive backstepping algorithm with its stability ensured by the Lyapunov stability theorem. As a reference controller for the backstepping method, a hybrid neural controller is introduced in which the linear motor itself is controlled by a conventional PI velocity controller and the vibration of the associated flexible mechanism is suppressed from an outer control loop using a compensation signal from a multilayer perceptron network. To avoid the local minimum problem entailed in neural networks, the initial weights are searched for offline by means of a differential evolution algorithm. The states of a mechanical system for controllers are estimated using the Kalman filter. The theoretical results obtained from the control design are validated with the lumped mass model for a mechanism. Generalization of the mechanism allows the methods derived here to be widely implemented in machine automation. The control algorithms are first designed in a specially introduced nonlinear simulation model and then implemented in the physical linear motor using a DSP (Digital Signal Processor) application. The measurements prove that both controllers are capable of suppressing vibration, but that the backstepping method is superior to others due to its accuracy of response and stability properties.

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The effective notch stress approach for the fatigue strength assessment of welded structures as included in the Fatigue Design Recommendation of the IIW requires the numerical analysis of the elastic notch stress in the weld toe and weld root which is fictitiously rounded with a radius of 1mm. The goal of this thesis work was to consider alternate meshing strategies when using the effective notch stress approach to assess the fatigue strength of load carrying partial penetration fillet-welded cruciform joints. In order to establish guidelines for modeling the joint and evaluating the results, various two-dimensional (2D) finite element analyses were carried out by systematically varying the thickness of the plates, the weld throat thickness, the degree of bending, and the shape and location of the modeled effective notch. To extend the scope of this work, studies were also carried out on the influence of

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To predict the capacity of the structure or the point which is followed by instability, calculation of the critical crack size is important. Structures usually contain several cracks but not necessarily all of these cracks lead to failure or reach the critical size. So, defining the harmful cracks or the crack size which is the most leading one to failure provides criteria for structure’s capacity at elevated temperature. The scope of this thesis was to calculate fracture parameters like stress intensity factor, the J integral and plastic and ultimate capacity of the structure to estimate critical crack size for this specific structure. Several three dimensional (3D) simulations using finite element method by Ansys program and boundary element method by Frank 3D program were carried out to calculate fracture parameters and results with the aid of laboratory tests (loaddisplacement curve, the J resistance curve and yield or ultimate stress) leaded to extract critical size of the crack. Two types of the fracture which is usually affected by temperature, Elastic and Elasti-Plastic fractures were simulated by performing several linear elastic and nonlinear elastic analyses. Geometry details of the weldment; flank angle and toe radius were also studied independently to estimate the location of crack initiation and simulate stress field in early stages of crack extension in structure. In this work also overview of the structure’s capacity in room temperature (20 ºC) was studied. Comparison of the results in different temperature (20 ºC and -40 ºC) provides a threshold of the structure’s behavior within the defined range.

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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.

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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.

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With the new age of Internet of Things (IoT), object of everyday such as mobile smart devices start to be equipped with cheap sensors and low energy wireless communication capability. Nowadays mobile smart devices (phones, tablets) have become an ubiquitous device with everyone having access to at least one device. There is an opportunity to build innovative applications and services by exploiting these devices’ untapped rechargeable energy, sensing and processing capabilities. In this thesis, we propose, develop, implement and evaluate LoadIoT a peer-to-peer load balancing scheme that can distribute tasks among plethora of mobile smart devices in the IoT world. We develop and demonstrate an android-based proof of concept load-balancing application. We also present a model of the system which is used to validate the efficiency of the load balancing approach under varying application scenarios. Load balancing concepts can be apply to IoT scenario linked to smart devices. It is able to reduce the traffic send to the Cloud and the energy consumption of the devices. The data acquired from the experimental outcomes enable us to determine the feasibility and cost-effectiveness of a load balanced P2P smart phone-based applications.