Error Modeling and Accuracy Analysis of a Novel Mobile Hybrid Parallel Robot

Over the last decades, calibration techniques have been widely used to improve the accuracy of robots and machine tools since they only involve software modification instead of changing the design and manufacture of the hardware. Traditionally, there are four steps are required for a calibration, i.e. error modeling, measurement, parameter identification and compensation. The objective of this thesis is to propose a method for the kinematics analysis and error modeling of a newly developed hybrid redundant robot IWR (Intersector Welding Robot), which possesses ten degrees of freedom (DOF) where 6-DOF in parallel and additional 4-DOF in serial. In this article, the problem of kinematics modeling and error modeling of the proposed IWR robot are discussed. Based on the vector arithmetic method, the kinematics model and the sensitivity model of the end-effector subject to the structure parameters is derived and analyzed. The relations between the pose (position and orientation) accuracy and manufacturing tolerances, actuation errors, and connection errors are formulated. Computer simulation is performed to examine the validity and effectiveness of the proposed method.

Estimation of existing cable systems in generator-busbar unit and choice the optimal solution for its modernization

The aim of this master’s thesis is to develop an algorithm to calculate the cable network for heat and power station CHGRES. This algorithm includes important aspect which has an influence on the cable network reliability. Moreover, according to developed algorithm, the optimal solution for modernization cable system from economical and technical point of view was obtained. The conditions of existing cable lines show that replacement is necessary. Otherwise, the fault situation would happen. In this case company would loss not only money but also its prestige. As a solution, XLPE single core cables are more profitable than other types of cable considered in this work. Moreover, it is presented the dependence of value of short circuit current on number of 10/110 kV transformers connected in parallel between main grid and considered 10 kV busbar and how it affects on final decision. Furthermore, the losses of company in power (capacity) market due to fault situation are presented. These losses are commensurable with investment to replace existing cable system.

Permanent Magnet Synchronous Machine for Parallel Hybrid Vehicle

The aim of this thesis is to describe hybrid drive design problems, the advantages and difficulties related to the drive. A review of possible hybrid constructions, benefits of parallel, series and series-parallel hybrids is done. In the thesis analytical and finite element calculations of permanent magnet synchronous machines with embedded magnets were done. The finite element calculations were done using Cedrat’s Flux 2D software. This machine is planned to be used as a motor-generator in a low power parallel hybrid vehicle. The boundary conditions for the design were found from Lucas-TVS Ltd., India. Design Requirements, briefly: • The system DC voltage level is 120 V, which implies Uphase = 49 V (RMS) in a three phase system. • The power output of 10 kW at base speed 1500 rpm (Torque of 65 Nm) is desired. • The maximum outer diameter should not be more than 250 mm, and the maximum core length should not exceed 40 mm. The main difficulties which the author met were the dimensional restrictions. After having designed and analyzed several possible constructions they were compared and the final design selected. Dimensioned and detailed design is performed. Effects of different parameters, such as the number of poles, number of turns and magnetic geometry are discussed. The best modification offers considerable reduction of volume.

On Undecidable Dynamical Properties of Reversible One-Dimensional Cellular Automata

Cellular automata are models for massively parallel computation. A cellular automaton consists of cells which are arranged in some kind of regular lattice and a local update rule which updates the state of each cell according to the states of the cell's neighbors on each step of the computation. This work focuses on reversible one-dimensional cellular automata in which the cells are arranged in a two-way in_nite line and the computation is reversible, that is, the previous states of the cells can be derived from the current ones. In this work it is shown that several properties of reversible one-dimensional cellular automata are algorithmically undecidable, that is, there exists no algorithm that would tell whether a given cellular automaton has the property or not. It is shown that the tiling problem of Wang tiles remains undecidable even in some very restricted special cases. It follows that it is undecidable whether some given states will always appear in computations by the given cellular automaton. It also follows that a weaker form of expansivity, which is a concept of dynamical systems, is an undecidable property for reversible one-dimensional cellular automata. It is shown that several properties of dynamical systems are undecidable for reversible one-dimensional cellular automata. It shown that sensitivity to initial conditions and topological mixing are undecidable properties. Furthermore, non-sensitive and mixing cellular automata are recursively inseparable. It follows that also chaotic behavior is an undecidable property for reversible one-dimensional cellular automata.

Stress testing and risk evaluation of new capacity payment algorithm proposed by Market Council

In the Russian Wholesale Market, electricity and capacity are traded separately. Capacity is a special good, the sale of which obliges suppliers to keep their generating equipment ready to produce the quantity of electricity indicated by the System Operator. The purpose of the formation of capacity trading was the maintenance of reliable and uninterrupted delivery of electricity in the wholesale market. The price of capacity reflects constant investments in construction, modernization and maintenance of power plants. So, the capacity sale creates favorable conditions to attract investments in the energy sector because it guarantees the investor that his investments will be returned.

Solving Leontief Input-Output Model with Trapezoidal Fuzzy Numbers and Gauss-Seidel Algorithm

In this work a fuzzy linear system is used to solve Leontief input-output model with fuzzy entries. For solving this model, we assume that the consumption matrix from di erent sectors of the economy and demand are known. These assumptions heavily depend on the information obtained from the industries. Hence uncertainties are involved in this information. The aim of this work is to model these uncertainties and to address them by fuzzy entries such as fuzzy numbers and LR-type fuzzy numbers (triangular and trapezoidal). Fuzzy linear system has been developed using fuzzy data and it is solved using Gauss-Seidel algorithm. Numerical examples show the e ciency of this algorithm. The famous example from Prof. Leontief, where he solved the production levels for U.S. economy in 1958, is also further analyzed.

GAMS MINLP Solver comparisons and some improvements to the AlphaECP algorithm

I doktorsavhandlingen undersöks förmågan att lösa hos ett antal lösare för optimeringsproblem och ett antal svårigheter med att göra en rättvis lösarjämförelse avslöjas. Dessutom framläggs några förbättringar som utförts på en av lösarna som heter GAMS/AlphaECP. Optimering innebär, i det här sammanhanget, att finna den bästa möjliga lösningen på ett problem. Den undersökta klassen av problem kan karaktäriseras som svårlöst och förekommer inom ett flertal industriområden. Målet har varit att undersöka om det finns en lösare som är universellt snabbare och hittar lösningar med högre kvalitet än någon av de andra lösarna. Det kommersiella optimeringssystemet GAMS (General Algebraic Modeling System) och omfattande problembibliotek har använts för att jämföra lösare. Förbättringarna som presenterats har utförts på GAMS/AlphaECP lösaren som baserar sig på skärplansmetoden Extended Cutting Plane (ECP). ECP-metoden har utvecklats främst av professor Tapio Westerlund på Anläggnings- och systemteknik vid Åbo Akademi.

Kaarihitsauksen suojakaasun tunnistus ja virtauksen mittaus ultraäänellä

Kaasukaarihitsauksessa suojakaasuna käytetään yleensä argonin ja hiilidioksidin tai argonin ja heliumin seoksia. Suojakaasu vaikuttaa useisiin hitsausominaisuuksiin, jotka puolestaan vaikuttavat hitsauksen laatuun ja tuottavuuteen. Automaattisella suojakaasun tunnistuksella ja virtausmäärän mittauksella voitaisiin tehdä hitsauksesta paitsi käyttäjän kannalta yksinkertaisempaa, myös laadukkaampaa. Työn tavoite on löytää mahdollisimman edullinen ja kuitenkin mahdollisimman tarkasti kaasuseoksia tunnistava menetelmä, jota voitaisiin hyödyntää MIG/MAG-hitsauskoneeseen sisäänrakennettuna. Selvä etu on, jos menetelmällä voidaan mitata myös kaasun virtausmäärä. Äänennopeus kaasumaisessa väliaineessa on aineen atomi- ja molekyylirakenteesta ja lämpötilasta riippuva ominaisuus, joka voidaan mitata melko edullisesti. Äänennopeuden määritys perustuu ääniaallon kulkuajan mittaamiseen tunnetun pituisella matkalla. Kaasun virtausnopeus on laskettavissa myötä- ja vastavirtaan mitattujen kulkuaikojen erotuksen avulla. Rakennettu mittauslaitteisto koostuu kahdesta ultraäänimuuntimesta, joiden halkaisija on 10 mm ja jotka toimivat sekä lähettimenä että vastaanottimena. Muuntimet ovat 140 mm:n etäisyydellä toisistaan virtauskanavassa, jossa suojakaasu virtaa yhdensuuntaisesti äänen kanssa. Virtauskanava on putki, jossa on käytetty elastisia materiaaleja, jotta ääniaaltojen eteneminen kanavan runkoa pitkin minimoituisi. Kehitetty algoritmi etsii kahden lähetetyn 40 kHz:n taajuisen kanttiaaltopulssin aiheuttaman vasteen perusteella ääniaallon saapumisajanhetken. Useiden mittausten, tulosten lajittelun ja suodatuksen jälkeen tuntemattomalle kaasulle lasketaan lämpötilakompensoitu vertailuluku. Tuntematon kaasu tunnistetaan vertailemalla lukua tunnettujen kaasuseosten mitattuihin vertailulukuihin. Laitteisto tunnistaa seokset, joissa heliumin osuus argonissa on enintään 50 %. Hiilidioksidia sisältävät argonin seokset puolestaan tunnistetaan puhtaaseen hiilidioksidiin asti jopa kahden prosenttiyksikön tarkkuudella. Kaasun tilavuusvirtausmittauksen tarkkuus on noin 1,0 l/min.

Design and Control of Permanent Magnet Synchronous Machine for Hybrid Electric Vehicle

This master’s thesis mainly focuses on the design requirements of an Electric drive for Hybrid car application and its control strategy to achieve a wide speed range. It also emphasises how the control and performance requirements are transformed into its design variables. A parallel hybrid topology is considered where an IC engine and an electric drive share a common crank shaft. A permanent magnet synchronous machine (PMSM) is used as an electric drive machine. Performance requirements are converted into Machine design variables using the vector model of PMSM. Main dimensions of the machine are arrived using analytical approach and Finite Element Analysis (FEA) is used to verify the design and performance. Vector control algorithm was used to control the machine. The control algorithm was tested in a low power PMSM using an embedded controller. A prototype of 10 kW PMSM was built according to the design values. The prototype was tested in the laboratory using a high power converter. Tests were carried out to verify different operating modes. The results were in agreement with the calculations.

Exploration and Design of Power-Efficient Networked Many-Core Systems

Multiprocessing is a promising solution to meet the requirements of near future applications. To get full benefit from parallel processing, a manycore system needs efficient, on-chip communication architecture. Networkon- Chip (NoC) is a general purpose communication concept that offers highthroughput, reduced power consumption, and keeps complexity in check by a regular composition of basic building blocks. This thesis presents power efficient communication approaches for networked many-core systems. We address a range of issues being important for designing power-efficient manycore systems at two different levels: the network-level and the router-level. From the network-level point of view, exploiting state-of-the-art concepts such as Globally Asynchronous Locally Synchronous (GALS), Voltage/ Frequency Island (VFI), and 3D Networks-on-Chip approaches may be a solution to the excessive power consumption demanded by today’s and future many-core systems. To this end, a low-cost 3D NoC architecture, based on high-speed GALS-based vertical channels, is proposed to mitigate high peak temperatures, power densities, and area footprints of vertical interconnects in 3D ICs. To further exploit the beneficial feature of a negligible inter-layer distance of 3D ICs, we propose a novel hybridization scheme for inter-layer communication. In addition, an efficient adaptive routing algorithm is presented which enables congestion-aware and reliable communication for the hybridized NoC architecture. An integrated monitoring and management platform on top of this architecture is also developed in order to implement more scalable power optimization techniques. From the router-level perspective, four design styles for implementing power-efficient reconfigurable interfaces in VFI-based NoC systems are proposed. To enhance the utilization of virtual channel buffers and to manage their power consumption, a partial virtual channel sharing method for NoC routers is devised and implemented. Extensive experiments with synthetic and real benchmarks show significant power savings and mitigated hotspots with similar performance compared to latest NoC architectures. The thesis concludes that careful codesigned elements from different network levels enable considerable power savings for many-core systems.

XII olympiad Helsinki 20th july - 4th august 1940 programme and prices of admission tickets

kuv., 14 x 22 cm

Simuloinnin hyödyntäminen kotihoidon kehittämisessä

Ikääntyvien ihmisten kasvava määrä tulevina vuosikymmeninä kuormittaa kaupunkien kotihoitoa enenemässä määrin. Kaupunkien rajalliset resurssit ovat jo nyt koetuksella, eikä nykyiseen tilanteeseen ole nähtävissä huomattavaa parannusta tulevina vuosina. Kotihoidon henkilöstön määrää ei pystytä kasvattamaan riittävästi suhteessa kasvavien asiakasvirtojen kanssa, jotta korkea palvelun laatu voitaisiin taata myös tulevaisuudessa. Lahden kaupungin kotihoito pyrkii etsimään teknisiä ratkaisuja kotihoidon haasteisiin muun muassa kotihoidon töiden jakamiseen kehitetyllä optimointialgoritmilla sekä simuloinnilla. Tämä diplomityö käsittelee toimintatutkimuksen avulla simuloinnin tuomia hyötyjä sekä rajoitteita Lahden kotihoidon näkökulmasta. Launeen alueen kotihoidon haasteita käydään läpi neljässä eri työpajassa. Työssä esitetään Quest-simulointiohjelmiston ominaisuuksia, sekä Launeen alueen simulointimallin luomista aina suunnittelusta verifiointiin. Työn tuottama lisäarvo kotihoidon kehittämisessä tulee ilmi neljässä eri vaihtoehtoajossa kotihoitajien asiakkaalta toiselle kulkemien matkojen ja matkoihin käytettyjen aikojen mittaamisessa.

Video transcoding in a distributed cloud computing environment

Video transcoding refers to the process of converting a digital video from one format into another format. It is a compute-intensive operation. Therefore, transcoding of a large number of simultaneous video streams requires a large amount of computing resources. Moreover, to handle di erent load conditions in a cost-e cient manner, the video transcoding service should be dynamically scalable. Infrastructure as a Service Clouds currently offer computing resources, such as virtual machines, under the pay-per-use business model. Thus the IaaS Clouds can be leveraged to provide a coste cient, dynamically scalable video transcoding service. To use computing resources e ciently in a cloud computing environment, cost-e cient virtual machine provisioning is required to avoid overutilization and under-utilization of virtual machines. This thesis presents proactive virtual machine resource allocation and de-allocation algorithms for video transcoding in cloud computing. Since users' requests for videos may change at di erent times, a check is required to see if the current computing resources are adequate for the video requests. Therefore, the work on admission control is also provided. In addition to admission control, temporal resolution reduction is used to avoid jitters in a video. Furthermore, in a cloud computing environment such as Amazon EC2, the computing resources are more expensive as compared with the storage resources. Therefore, to avoid repetition of transcoding operations, a transcoded video needs to be stored for a certain time. To store all videos for the same amount of time is also not cost-e cient because popular transcoded videos have high access rate while unpopular transcoded videos are rarely accessed. This thesis provides a cost-e cient computation and storage trade-o strategy, which stores videos in the video repository as long as it is cost-e cient to store them. This thesis also proposes video segmentation strategies for bit rate reduction and spatial resolution reduction video transcoding. The evaluation of proposed strategies is performed using a message passing interface based video transcoder, which uses a coarse-grain parallel processing approach where video is segmented at group of pictures level.

Energy-efficient control strategies for variable speed driven parallel pumping systems based on pump operation point monitoring with frequency converters

The pumping processes requiring wide range of flow are often equipped with parallelconnected centrifugal pumps. In parallel pumping systems, the use of variable speed control allows that the required output for the process can be delivered with a varying number of operated pump units and selected rotational speed references. However, the optimization of the parallel-connected rotational speed controlled pump units often requires adaptive modelling of both parallel pump characteristics and the surrounding system in varying operation conditions. The available information required for the system modelling in typical parallel pumping applications such as waste water treatment and various cooling and water delivery pumping tasks can be limited, and the lack of real-time operation point monitoring often sets limits for accurate energy efficiency optimization. Hence, alternatives for easily implementable control strategies which can be adopted with minimum system data are necessary. This doctoral thesis concentrates on the methods that allow the energy efficient use of variable speed controlled parallel pumps in system scenarios in which the parallel pump units consist of a centrifugal pump, an electric motor, and a frequency converter. Firstly, the suitable operation conditions for variable speed controlled parallel pumps are studied. Secondly, methods for determining the output of each parallel pump unit using characteristic curve-based operation point estimation with frequency converter are discussed. Thirdly, the implementation of the control strategy based on real-time pump operation point estimation and sub-optimization of each parallel pump unit is studied. The findings of the thesis support the idea that the energy efficiency of the pumping can be increased without the installation of new, more efficient components in the systems by simply adopting suitable control strategies. An easily implementable and adaptive control strategy for variable speed controlled parallel pumping systems can be created by utilizing the pump operation point estimation available in modern frequency converters. Hence, additional real-time flow metering, start-up measurements, and detailed system model are unnecessary, and the pumping task can be fulfilled by determining a speed reference for each parallel-pump unit which suggests the energy efficient operation of the pumping system.

Cost-efficient virtual machine management : provisioning, admission control, and consolidation

One of the main challenges in Software Engineering is to cope with the transition from an industry based on software as a product to software as a service. The field of Software Engineering should provide the necessary methods and tools to develop and deploy new cost-efficient and scalable digital services. In this thesis, we focus on deployment platforms to ensure cost-efficient scalability of multi-tier web applications and on-demand video transcoding service for different types of load conditions. Infrastructure as a Service (IaaS) clouds provide Virtual Machines (VMs) under the pay-per-use business model. Dynamically provisioning VMs on demand allows service providers to cope with fluctuations on the number of service users. However, VM provisioning must be done carefully, because over-provisioning results in an increased operational cost, while underprovisioning leads to a subpar service. Therefore, our main focus in this thesis is on cost-efficient VM provisioning for multi-tier web applications and on-demand video transcoding. Moreover, to prevent provisioned VMs from becoming overloaded, we augment VM provisioning with an admission control mechanism. Similarly, to ensure efficient use of provisioned VMs, web applications on the under-utilized VMs are consolidated periodically. Thus, the main problem that we address is cost-efficient VM provisioning augmented with server consolidation and admission control on the provisioned VMs. We seek solutions for two types of applications: multi-tier web applications that follow the request-response paradigm and on-demand video transcoding that is based on video streams with soft realtime constraints. Our first contribution is a cost-efficient VM provisioning approach for multi-tier web applications. The proposed approach comprises two subapproaches: a reactive VM provisioning approach called ARVUE and a hybrid reactive-proactive VM provisioning approach called Cost-efficient Resource Allocation for Multiple web applications with Proactive scaling. Our second contribution is a prediction-based VM provisioning approach for on-demand video transcoding in the cloud. Moreover, to prevent virtualized servers from becoming overloaded, the proposed VM provisioning approaches are augmented with admission control approaches. Therefore, our third contribution is a session-based admission control approach for multi-tier web applications called adaptive Admission Control for Virtualized Application Servers. Similarly, the fourth contribution in this thesis is a stream-based admission control and scheduling approach for on-demand video transcoding called Stream-Based Admission Control and Scheduling. Our fifth contribution is a computation and storage trade-o strategy for cost-efficient video transcoding in cloud computing. Finally, the sixth and the last contribution is a web application consolidation approach, which uses Ant Colony System to minimize the under-utilization of the virtualized application servers.