Keskipakoispuhaltimen siipipyörän lujuusteknisen mitoituksen kehittäminen

Tässä työssä on tutkittu prosessipuhaltimena käytettävän keskipakoispuhaltimen lujuusteknistä mitoitusta. Työn tavoitteena on ollut luoda analyyttisiä laskentakaavoja Koja Oy:n käyttöön tulevaisuuden tuotekehityksen tueksi. Tavoitteena on ollut tutkia myös siipien ja etu- ja takalevyn kiinnityshitsejä ja antaa työkaluja siipipyörän väsymismitoitukseen. Kirjallisuuskatkauksessa löytyi muutamia raportoituja tapauksia, jossa keskipakoispuhallin on vaurioitunut käytön aikana. Yhtenäisenä tekijänä kaikille tapauksille on ollut hitsausliitoksen väsyminen. Väsyttävän kuormituksen raportoiduissa tapauksissa on aiheuttanut siipipyörän värähtely. Väsyminen on alkanut siiven kiinnitysliitoksista hitsin rajaviivalta, siipipyörän ulkokehältä. Siipipyörän analysointiin on käytetty analyyttisiä laskentakaavoja ja elementtimenetelmää. Analyyttisten laskentakaavojen tuottaminen on muuten monimutkaiselle rakenteelle hyvin työlästä ja aikaa vievää. Staattisessa tarkastelussa elementtimenetelmällä siipipyörän mallintamiseen on käytetty keskipintamallia. Lisäksi laskentatiedostojen kokoa on pystytty rajaamaan syklisesti symmetrisen rakenteen ansiosta. Siipipyörän väsymistarkastelu on suoritettu tehollisen lovijännityksen menetelmällä, jossa tarkasteltavan hitsin rajaviivoille ja juureen on elementtimenetelmässä mallinnettu r=1 mm suuruinen lovi, josta jännityksen on luettu. Elementtimenetelmässä laskentaohjelmistona on käytetty Abaqus 6.14.1 -laskentaohjelmistoa. Analyyttisten laskentakaavojen kehityksessä on päästy hyvin lähelle elementtimenetelmästä saatuja vastaavia tuloksia. Analyyttisten kaavojen antamat tulokset eroavat kuitenkin sen verran virhettä, että varsinainen tarkka laskenta on syytä suorittaa ennen lopullisen konstruktion määrittämistä. Tehollisella lovijännitysmenetelmällä on saatu määritettyä rakenteen kriittisin kohta, jonka kestoikä on 36 400 sykliä. Tutkimuksen pohjalta Koja Oy on saanut hyvät edellytykset jatkaa tutkimusta lopun tuoteperheen parantamiseen.

On-Line Analytical Processing of Inventory Turnover

Operatiivisen tiedon tuottaminen loppukäyttäjille analyyttistä tarkastelua silmällä pitäen aiheuttaa ongelmia useille yrityksille. Diplomityö pyrkii ratkaisemaan ko. ongelman Teleste Oyj:ssä. Työ on jaettu kolmeen pääkappaleeseen. Kappale 2 selkiyttää On-Line Analytical Processing (OLAP)- käsitteen. Kappale 3 esittelee muutamia OLAP-tuotteiden valmistajia ja heidän arkkitehtuurejaan sekä tyypillisten sovellusalueiden lisäksi huomioon otettavia asioita OLAP käyttöönoton yhteydessä. Kappale 4, tuo esille varsinaisen ratkaisun. Teknisellä arkkitehtuurilla on merkittävä asema ratkaisun rakenteen kannalta. Tässä on sovellettu Microsoft:n tietovarasto kehysrakennetta. Kappaleen 4 edetessä, tapahtumakäsittelytieto muutetaan informaatioksi ja edelleen loppukäyttäjien tiedoksi. Loppukäyttäjät varustetaan tehokkaalla ja tosiaikaisella analysointityökalulla moniulotteisessa ympäristössä. Vaikka kiertonopeus otetaan työssä sovellusesimerkiksi, työ ei pyri löytämään optimaalista tasoa Telesten varastoille. Siitä huolimatta eräitä parannusehdotuksia mainitaan.

Analytical Study on the Influence of Geometrical Parameters on the Fatigue Strength of Welds with Undercuts

The purpose of this study is to analyze the influence of geometric parameters on the fatigue strength of the welded joint. The thesis includes the analytical study pertaining to variation of undercut and the weld toe radius. The theoretical part includes the concepts of fracture mechanics, different stages of the crack propagation and finally the results. The numerical results are obtained from FRANC2D/L. The results show that the fatigue strength of the welded structure depends on the parameters of the welds such as the weld toe radius, weld angle, height of the undercut and plate thickness. The results show that the fatigue life can be improved by having the undercut as minimum as possible. However there has been significant variation on the fatigue life of the structure when the weld toe radius is increased.

Matrix Analytic Analysis of Delays in Communication Systems

Tässä päättötyössä annetaan kuvaus kehitetystä sovelluksesta Quasi Birth Death processien ratkaisuun. Tämä ohjelma on tähän mennessä ainutlaatuinen ja sen avulla voi ratkaista sarjan tehtäviä ja sitä tarvitaan kommunikaatio systeemien analyysiin. Mainittuun sovellukseen on annettu kuvaus ja määritelmä. Lyhyt kuvaus toisesta sovelluksesta Quasi Birth Death prosessien tehtävien ratkaisuun on myös annettu

Supplier Evaluation Using Analytical Hierarchy Process

The goal of the thesis is to make a supplier evaluation using analytical hierarchy process. Before the supplier evaluation is performed there will be introduced the principles of purchasing which gives a viewpoint to the supplier evaluation and management. The thesis will also give an overview on quality, performance and forecasts which are very important to the supplier evaluation and future improvements. The chapter which describes analytical hierarchy process will show the reader what exactly is analytical hierarchy process and how can it be utilized in supplier evaluation. In the later stages, thesis will provide information about the case company EADS Secure Networks Oy, the processes applied there towards purchasing and how the analytical hierarchy process is applied in practise. In the end of the thesis there will be an overview about each supplier’s strong and weak points as well as some comments and ideas about developing also EADS Secure Networks procedures to a direction which would benefit the whole customer–supplier–chain.

New Distance Transforms for Gray Level Image Compression

This thesis deals with distance transforms which are a fundamental issue in image processing and computer vision. In this thesis, two new distance transforms for gray level images are presented. As a new application for distance transforms, they are applied to gray level image compression. The new distance transforms are both new extensions of the well known distance transform algorithm developed by Rosenfeld, Pfaltz and Lay. With some modification their algorithm which calculates a distance transform on binary images with a chosen kernel has been made to calculate a chessboard like distance transform with integer numbers (DTOCS) and a real value distance transform (EDTOCS) on gray level images. Both distance transforms, the DTOCS and EDTOCS, require only two passes over the graylevel image and are extremely simple to implement. Only two image buffers are needed: The original gray level image and the binary image which defines the region(s) of calculation. No other image buffers are needed even if more than one iteration round is performed. For large neighborhoods and complicated images the two pass distance algorithm has to be applied to the image more than once, typically 3 10 times. Different types of kernels can be adopted. It is important to notice that no other existing transform calculates the same kind of distance map as the DTOCS. All the other gray weighted distance function, GRAYMAT etc. algorithms find the minimum path joining two points by the smallest sum of gray levels or weighting the distance values directly by the gray levels in some manner. The DTOCS does not weight them that way. The DTOCS gives a weighted version of the chessboard distance map. The weights are not constant, but gray value differences of the original image. The difference between the DTOCS map and other distance transforms for gray level images is shown. The difference between the DTOCS and EDTOCS is that the EDTOCS calculates these gray level differences in a different way. It propagates local Euclidean distances inside a kernel. Analytical derivations of some results concerning the DTOCS and the EDTOCS are presented. Commonly distance transforms are used for feature extraction in pattern recognition and learning. Their use in image compression is very rare. This thesis introduces a new application area for distance transforms. Three new image compression algorithms based on the DTOCS and one based on the EDTOCS are presented. Control points, i.e. points that are considered fundamental for the reconstruction of the image, are selected from the gray level image using the DTOCS and the EDTOCS. The first group of methods select the maximas of the distance image to new control points and the second group of methods compare the DTOCS distance to binary image chessboard distance. The effect of applying threshold masks of different sizes along the threshold boundaries is studied. The time complexity of the compression algorithms is analyzed both analytically and experimentally. It is shown that the time complexity of the algorithms is independent of the number of control points, i.e. the compression ratio. Also a new morphological image decompression scheme is presented, the 8 kernels' method. Several decompressed images are presented. The best results are obtained using the Delaunay triangulation. The obtained image quality equals that of the DCT images with a 4 x 4

Eddy-current losses in rotor surface mounted permanent magnets

The aim of the work is to study the existing analytical calculation procedures found in literature to calculate the eddy-current losses in surface mounted permanent magnets within PMSM application. The most promising algorithms are implemented with MATLAB software under the dimensional data of LUT prototype machine. In addition finite elements analyze, utilized with help of Flux 2D software from Cedrat Ltd, is applied to calculate the eddy-current losses in permanent magnets. The results obtained from analytical methods are compared with numerical results.

MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

Quasi allegro

Soitinnus: lauluääni, piano.

Comparison Structure Analysis

This study presents an automatic, computer-aided analytical method called Comparison Structure Analysis (CSA), which can be applied to different dimensions of music. The aim of CSA is first and foremost practical: to produce dynamic and understandable representations of musical properties by evaluating the prevalence of a chosen musical data structure through a musical piece. Such a comparison structure may refer to a mathematical vector, a set, a matrix or another type of data structure and even a combination of data structures. CSA depends on an abstract systematic segmentation that allows for a statistical or mathematical survey of the data. To choose a comparison structure is to tune the apparatus to be sensitive to an exclusive set of musical properties. CSA settles somewhere between traditional music analysis and computer aided music information retrieval (MIR). Theoretically defined musical entities, such as pitch-class sets, set-classes and particular rhythm patterns are detected in compositions using pattern extraction and pattern comparison algorithms that are typical within the field of MIR. In principle, the idea of comparison structure analysis can be applied to any time-series type data and, in the music analytical context, to polyphonic as well as homophonic music. Tonal trends, set-class similarities, invertible counterpoints, voice-leading similarities, short-term modulations, rhythmic similarities and multiparametric changes in musical texture were studied. Since CSA allows for a highly accurate classification of compositions, its methods may be applicable to symbolic music information retrieval as well. The strength of CSA relies especially on the possibility to make comparisons between the observations concerning different musical parameters and to combine it with statistical and perhaps other music analytical methods. The results of CSA are dependent on the competence of the similarity measure. New similarity measures for tonal stability, rhythmic and set-class similarity measurements were proposed. The most advanced results were attained by employing the automated function generation – comparable with the so-called genetic programming – to search for an optimal model for set-class similarity measurements. However, the results of CSA seem to agree strongly, independent of the type of similarity function employed in the analysis.

Quasi-objects and actors in the web of belief. Formation of a national nuclear waste management system: the case of Finland

Paper presented in ISA RC23 meeting, Gothenburg July 16th 2010

Numerics of Spacecraft Dynamics

Whenever a spacecraft is launched it is essential that the algorithms in the on-board software systems and at ground control are efficient and reliable over extended periods of time. Geometric numerical integrators, and in particular variational integrators, have both these characteristics. In "Numerics of Spacecraft Dynamics" new numerical integrators are presented and analysed in depth. These algorithms have been designed specifically for the dynamics of spacecraft and artificial satellites in Earth orbits. Full analytical solutions to a class of integrable deformations of the two-body problem in classical mechanics are derived, and a systematic method to compute variational integrators to arbitrary order with a computer algebra system is introduced.