89 resultados para Numerical optimization


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The purpose of this thesis was to create design a guideline for an LCL-filter. This thesis reviews briefly the relevant harmonics standards, old filter designs and problems faced with the previous filters. This thesis proposes a modified design method based on the “Liserre’s method” presented in the literature. This modified method will take into account network parameters better. As input parameters, the method uses the nominal power, allowed ripple current in converter and network side and desired resonant frequency of the filter. Essential component selection issues for LCL-filter, such as heating, voltage strength, current rating etc. are also discussed. Furthermore, a simulation model used to verify the operation of the designed filter in nominal power use and in transient situations is included in this thesis.

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The goal of the Master’s thesis is to develop and to analyze the optimization method for finding a geometry shape of classical horizontal wind turbine blades based on set of criteria. The thesis develops a technique that allows the designer to determine the weight of such factors as power coefficient, sound pressure level and the cost function in the overall process of blade shape optimization. The optimization technique applies the Desirability function. It was never used before in that kind of technical problems, and in this sense it can claim to originality of research. To do the analysis and the optimization processes more convenient the software application was developed.

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The demand for electricity is constantly growing in contemporary world and, in the same time, quality and reliability requirements are becoming more rigid. In addition, renewable sources of energy have been widely introduced for power generation, and they create specific challenges for the network. Consequently, new solution for distribution system is required, and Low Voltage Direct Current (LVDC) system is the proposed one. This thesis focuses on the investigation of specific cable features for low voltage direct current (LVDC) distribution system. The LVDC system is public ±750 VDC distribution system, which is currently being developed at Lappeen-ranta University of Technology. The aspects, considered in the thesis, are reliable and economic power transmission in distribution networks and possible power line communication in the LVDC cable.

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Supersonic axial turbine stages typically exhibit lower efficiencies than subsonic axial turbine stages. One reason for the lower efficiency is the occurrence of shock waves. With higher pressure ratios the flow inside the turbine becomes relatively easily supersonic if there is only one turbine stage. Supersonic axial turbines can be designed in smaller physical size compared to subsonic axial turbines of same power. This makes them good candidates for turbochargers in large diesel engines, where space can be a limiting factor. Also the production costs are lower for a supersonic axial turbine stage than for two subsonic stages. Since supersonic axial turbines are typically low reaction turbines, they also create lower axial forces to be compensated with bearings compared to high reaction turbines. The effect of changing the stator-rotor axial gap in a small high (rotational) speed supersonic axial flow turbine is studied in design and off-design conditions. Also the effect of using pulsatile mass flow at the supersonic stator inlet is studied. Five axial gaps (axial space between stator and rotor) are modeled using threedimensional computational fluid dynamics at the design and three axial gaps at the off-design conditions. Numerical reliability is studied in three independent studies. An additional measurement is made with the design turbine geometry at intermediate off-design conditions and is used to increase the reliability of the modelling. All numerical modelling is made with the Navier-Stokes solver Finflo employing Chien’s k ¡ ² turbulence model. The modelling of the turbine at the design and off-design conditions shows that the total-to-static efficiency of the turbine decreases when the axial gap is increased in both design and off-design conditions. The efficiency drops almost linearily at the off-design conditions, whereas the efficiency drop accelerates with increasing axial gap at the design conditions. The modelling of the turbine stator with pulsatile inlet flow reveals that the mass flow pulsation amplitude is decreased at the stator throat. The stator efficiency and pressure ratio have sinusoidal shapes as a function of time. A hysteresis-like behaviour is detected for stator efficiency and pressure ratio as a function of inlet mass flow, over one pulse period. This behaviour arises from the pulsatile inlet flow. It is important to have the smallest possible axial gap in the studied turbine type in order to maximize the efficiency. The results for the whole turbine can also be applied to some extent in similar turbines operating for example in space rocket engines. The use of a supersonic stator in a pulsatile inlet flow is shown to be possible.

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Transitional flow past a three-dimensional circular cylinder is a widely studied phenomenon since this problem is of interest with respect to many technical applications. In the present work, the numerical simulation of flow past a circular cylinder, performed by using a commercial CFD code (ANSYS Fluent 12.1) with large eddy simulation (LES) and RANS (κ - ε and Shear-Stress Transport (SST) κ - ω! model) approaches. The turbulent flow for ReD = 1000 & 3900 is simulated to investigate the force coefficient, Strouhal number, flow separation angle, pressure distribution on cylinder and the complex three dimensional vortex shedding of the cylinder wake region. The numerical results extracted from these simulations have good agreement with the experimental data (Zdravkovich, 1997). Moreover, grid refinement and time-step influence have been examined. Numerical calculations of turbulent cross-flow in a staggered tube bundle continues to attract interest due to its importance in the engineering application as well as the fact that this complex flow represents a challenging problem for CFD. In the present work a time dependent simulation using κ – ε, κ - ω! and SST models are performed in two dimensional for a subcritical flow through a staggered tube bundle. The predicted turbulence statistics (mean and r.m.s velocities) have good agreement with the experimental data (S. Balabani, 1996). Turbulent quantities such as turbulent kinetic energy and dissipation rate are predicted using RANS models and compared with each other. The sensitivity of grid and time-step size have been analyzed. Model constants sensitivity study have been carried out by adopting κ – ε model. It has been observed that model constants are very sensitive to turbulence statistics and turbulent quantities.

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En del av de intressantaste fenomenen inom dagens materialfysik uppstår ur ett intrikat samspel mellan myriader av elektroner. Högtemperatursupraledare är det mest berömda exemplet. Varken klassiska teorier eller modeller där elektronerna är oberoende av varandra kan förklara de häpnadsväckande effekterna i de starkt korrelerade elektronsystemen. I vissa kopparoxider, till exempel La2CuO4, är det känt att valenselektronerna till följd av en stark ömsesidig växelverkan lokaliseras en och en till kopparatomerna i föreningens CuO2 plan. Laddningarnas inneboende magnetiska moment—spinnet—får då en avgörande roll för materialets elektriska och magnetiska egenskaper, vilka i exemplets fall kan beskrivas med Heisenbergmodellen som är den grundläggande teoretiska modellen för mikroskopisk magnetism. Men exakt varför föreningarna kan bli supraledande då de dopas med överskottsladdningar är än så länge en obesvarad fråga. Min avhandling undersöker orenheters inverkan på Heisenbergmodellens magnetiska egenskaper—ett problem av både experimentell och teoretisk relevans. En etablerad numerisk metod har använts—en kvantmekanisk Monte Carlo teknik—för att utföra omfattande datorsimuleringar av den matematiska modellen på två dedikerade Linux datorkluster. Arbetet hör till området beräkningsfysik. De teoretiska modellerna för starkt korrelerade elektronsystem, däribland Heisenbergmodellen, är ytterst invecklade matematiskt sett och de kan inte lösas exakt. Analytiska utredningar bygger för det mesta på antaganden och förenklingar vars inverkningar på slutresultatet är ofta oklara. I det avseende kan numeriska studier vara exakta, det vill säga de kan behandla modellerna som de är. Oftast behövs bägge tillvägagångssätten. Den röda tråden i arbetet har varit att numeriskt testa vissa högaktuella analytiska förutsägelser rörande effekterna av orenheter i Heisenbergmodellen. En del av dem har vi på basen av mycket noggranna data kunnat bekräfta. Men våra resultat har också påvisat felaktigheter i de analytiska prognoserna som sedermera delvis reviderats. En del av avhandlingens numeriska upptäckter har i sin tur stimulerat till helt nya teoretiska studier.

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A company’s competence to manage its product portfolio complexity is becoming critically important in the rapidly changing business environment. The continuous evolvement of customer needs, the competitive market environment and internal product development lead to increasing complexity in product portfolios. The companies that manage the complexity in product development are more profitable in the long run. The complexity derives from product development and management processes where the new product variant development is not managed efficiently. Complexity is managed with modularization which is a method that divides the product structure into modules. In modularization, it is essential to take into account the trade-off between the perceived customer value and the module or component commonality across the products. Another goal is to enable the product configuration to be more flexible. The benefits are achieved through optimizing complexity in module offering and deriving the new product variants more flexibly and accurately. The developed modularization process includes the process steps for preparation, mapping the current situation, the creation of a modular strategy and implementing the strategy. Also the organization and support systems have to be adapted to follow-up targets and to execute modularization in practice.

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Preference relations, and their modeling, have played a crucial role in both social sciences and applied mathematics. A special category of preference relations is represented by cardinal preference relations, which are nothing other than relations which can also take into account the degree of relation. Preference relations play a pivotal role in most of multi criteria decision making methods and in the operational research. This thesis aims at showing some recent advances in their methodology. Actually, there are a number of open issues in this field and the contributions presented in this thesis can be grouped accordingly. The first issue regards the estimation of a weight vector given a preference relation. A new and efficient algorithm for estimating the priority vector of a reciprocal relation, i.e. a special type of preference relation, is going to be presented. The same section contains the proof that twenty methods already proposed in literature lead to unsatisfactory results as they employ a conflicting constraint in their optimization model. The second area of interest concerns consistency evaluation and it is possibly the kernel of the thesis. This thesis contains the proofs that some indices are equivalent and that therefore, some seemingly different formulae, end up leading to the very same result. Moreover, some numerical simulations are presented. The section ends with some consideration of a new method for fairly evaluating consistency. The third matter regards incomplete relations and how to estimate missing comparisons. This section reports a numerical study of the methods already proposed in literature and analyzes their behavior in different situations. The fourth, and last, topic, proposes a way to deal with group decision making by means of connecting preference relations with social network analysis.

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Min avhandling behandlar hur oordnade material leder elektrisk ström. Bland materialen som studeras finns ledande polymerer, d.v.s. plaster som leder ström, och mer allmänt organiska halvledare. Av de här materialen har man kunnat bygga elektroniska komponenter, och man hoppas på att kunna trycka hela kretsar av organiska material. För de här tillämpningarna är det viktigt att förstå hur materialen själva leder elektrisk ström. Termen oordnade material syftar på material som saknar kristallstruktur. Oordningen gör att elektronernas tillstånd blir lokaliserade i rummet, så att en elektron i ett visst tillstånd är begränsad t.ex. till en molekyl eller ett segment av en polymer. Det här kan jämföras med kristallina material, där ett elektrontillstånd är utspritt över hela kristallen (men i stället har en väldefinierad rörelsemängd). Elektronerna (eller hålen) i det oordnade materialet kan röra sig genom att tunnelera mellan de lokaliserade tillstånden. Utgående från egenskaperna för den här tunneleringsprocessen, kan man bestämma transportegenskaperna för hela materialet. Det här är utgångspunkten för den så kallade hopptransportmodellen, som jag har använt mig av. Hopptransportmodellen innehåller flera drastiska förenklingar. Till exempel betraktas elektrontillstånden som punktformiga, så att tunneleringssannolikheten mellan två tillstånd endast beror på avståndet mellan dem, och inte på deras relativa orientation. En annan förenkling är att behandla det kvantmekaniska tunneleringsproblemet som en klassisk process, en slumpvandring. Trots de här grova approximationerna visar hopptransportmodellen ändå många av de fenomen som uppträder i de verkliga materialen som man vill modellera. Man kan kanske säga att hopptransportmodellen är den enklaste modell för oordnade material som fortfarande är intressant att studera. Man har inte hittat exakta analytiska lösningar för hopptransportmodellen, därför använder man approximationer och numeriska metoder, ofta i form av datorberäkningar. Vi har använt både analytiska metoder och numeriska beräkningar för att studera olika aspekter av hopptransportmodellen. En viktig del av artiklarna som min avhandling baserar sig på är att jämföra analytiska och numeriska resultat. Min andel av arbetet har främst varit att utveckla de numeriska metoderna och applicera dem på hopptransportmodellen. Därför fokuserar jag på den här delen av arbetet i avhandlingens introduktionsdel. Ett sätt att studera hopptransportmodellen numeriskt är att direkt utföra en slumpvandringsprocess med ett datorprogram. Genom att föra statisik över slumpvandringen kan man beräkna olika transportegenskaper i modellen. Det här är en så kallad Monte Carlo-metod, eftersom själva beräkningen är en slumpmässig process. I stället för att följa rörelsebanan för enskilda elektroner, kan man beräkna sannolikheten vid jämvikt för att hitta en elektron i olika tillstånd. Man ställer upp ett system av ekvationer, som relaterar sannolikheterna för att hitta elektronen i olika tillstånd i systemet med flödet, strömmen, mellan de olika tillstånden. Genom att lösa ekvationssystemet fås sannolikhetsfördelningen för elektronerna. Från sannolikhetsfördelningen kan sedan strömmen och materialets transportegenskaper beräknas. En aspekt av hopptransportmodellen som vi studerat är elektronernas diffusion, d.v.s. deras slumpmässiga rörelse. Om man betraktar en samling elektroner, så sprider den med tiden ut sig över ett större område. Det är känt att diffusionshastigheten beror av elfältet, så att elektronerna sprider sig fortare om de påverkas av ett elektriskt fält. Vi har undersökt den här processen, och visat att beteendet är väldigt olika i endimensionella system, jämfört med två- och tredimensionella. I två och tre dimensioner beror diffusionskoefficienten kvadratiskt av elfältet, medan beroendet i en dimension är linjärt. En annan aspekt vi studerat är negativ differentiell konduktivitet, d.v.s. att strömmen i ett material minskar då man ökar spänningen över det. Eftersom det här fenomenet har uppmätts i organiska minnesceller, ville vi undersöka om fenomenet också kan uppstå i hopptransportmodellen. Det visade sig att det i modellen finns två olika mekanismer som kan ge upphov till negativ differentiell konduktivitet. Dels kan elektronerna fastna i fällor, återvändsgränder i systemet, som är sådana att det är svårare att ta sig ur dem då elfältet är stort. Då kan elektronernas medelhastighet och därmed strömmen i materialet minska med ökande elfält. Elektrisk växelverkan mellan elektronerna kan också leda till samma beteende, genom en så kallad coulombblockad. En coulombblockad kan uppstå om antalet ledningselektroner i materialet ökar med ökande spänning. Elektronerna repellerar varandra och ett större antal elektroner kan leda till att transporten blir långsammare, d.v.s. att strömmen minskar.

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In any decision making under uncertainties, the goal is mostly to minimize the expected cost. The minimization of cost under uncertainties is usually done by optimization. For simple models, the optimization can easily be done using deterministic methods.However, many models practically contain some complex and varying parameters that can not easily be taken into account using usual deterministic methods of optimization. Thus, it is very important to look for other methods that can be used to get insight into such models. MCMC method is one of the practical methods that can be used for optimization of stochastic models under uncertainty. This method is based on simulation that provides a general methodology which can be applied in nonlinear and non-Gaussian state models. MCMC method is very important for practical applications because it is a uni ed estimation procedure which simultaneously estimates both parameters and state variables. MCMC computes the distribution of the state variables and parameters of the given data measurements. MCMC method is faster in terms of computing time when compared to other optimization methods. This thesis discusses the use of Markov chain Monte Carlo (MCMC) methods for optimization of Stochastic models under uncertainties .The thesis begins with a short discussion about Bayesian Inference, MCMC and Stochastic optimization methods. Then an example is given of how MCMC can be applied for maximizing production at a minimum cost in a chemical reaction process. It is observed that this method performs better in optimizing the given cost function with a very high certainty.

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Optimointi on tavallinen toimenpide esimerkiksi prosessin muuttamisen tai uusimisen jälkeen. Optimoinnilla pyritään etsimään vaikkapa tiettyjen laatuominaisuuksien kannalta paras tapa ajaa prosessia tai erinäisiä prosessin osia. Tämän työn tarkoituksena oli investoinnin jälkeen optimoida neljä muuttujaa, erään runkoon menevän massan jauhatus ja määrä, märkäpuristus sekä spray –tärkin määrä, kolmen laatuominaisuuden, palstautumislujuuden, geometrisen taivutusjäykkyyden ja sileyden, suhteen. Työtä varten tehtiin viisi tehdasmittakaavaista koeajoa. Ensimmäisessä koeajossa oli tarkoitus lisätä vettä tai spray –tärkkiä kolmikerroskartongin toiseen kerrosten rajapintaan, toisessa koeajossa muutettiin, jo aiemmin mainitun runkoon menevän massan jauhatusta ja jauhinkombinaatioita. Ensimmäisessä koeajossa tutkittiin palstautumislujuuden, toisessa koeajossa muiden lujuusominaisuuksien kehittymistä. Kolmannessa koeajossa tutkittiin erään runkoon menevän massan jauhatuksen ja määrän sekä kenkäpuristimen viivapaineen muutoksen vaikutusta palstautumislujuuteen, geometriseen taivutusjäykkyyteen sekä sileyteen. Neljännessä koeajossa yritettiin toistaa edellisen koeajon paras piste ja parametreja hieman muuttamalla saada aikaan vieläkin paremmat laatuominaisuudet. Myös tässä kokeessa tutkittiin muuttujien vaikutusta palstautumislujuuteen, geometriseen taivutusjäykkyyteen ja sileyteen. Viimeisen kokeen tarkoituksena oli tutkia samaisen runkoon menevän massan vähentämisen vaikutusta palstautumislujuuteen. Erinäisistä vastoinkäymisistä johtuen, koeajoista saadut tulokset jäivät melko laihoiksi. Kokeista kävi kuitenkin ilmi, että lujuusominaisuudet eivät parantuneet, vaikka jauhatusta jatkettiin. Lujuusominaisuuksien kehittymisen kannalta turha jauhatus pystyttiin siis jättämään pois ja näin säästämään energiaa sekä säästymään pitkälle viedyn jauhatuksen mahdollisesti aiheuttamilta muilta ongelmilta. Vähemmällä jauhatuksella ominaissärmäkuorma saatiin myös pidettyä alle tehtaalla halutun tason. Puuttuvat lujuusominaisuudet täytyy saavuttaa muilla keinoin.

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Search engine optimization & marketing is a set of processes widely used on websites to improve search engine rankings which generate quality web traffic and increase ROI. Content is the most important part of any website. CMS web development is now become very essential for most of organizations and online businesses to develop their online system and websites. Every online business using a CMS wants to get users (customers) to make profit and ROI. This thesis comprises a brief study of existing SEO methods, tools and techniques and how they can be implemented to optimize a content base website. In results, the study provides recommendations about how to use SEO methods; tools and techniques to optimize CMS based websites on major search engines. This study compares popular CMS systems like Drupal, WordPress and Joomla SEO features and how implementing SEO can be improved on these CMS systems. Having knowledge of search engine indexing and search engine working is essential for a successful SEO campaign. This work is a complete guideline for web developers or SEO experts who want to optimize a CMS based website on all major search engines.

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The purpose of this study was to simulate and to optimize integrated gasification for combine cycle (IGCC) for power generation and hydrogen (H2) production by using low grade Thar lignite coal and cotton stalk. Lignite coal is abundant of moisture and ash content, the idea of addition of cotton stalk is to increase the mass of combustible material per mass of feed use for the process, to reduce the consumption of coal and to increase the cotton stalk efficiently for IGCC process. Aspen plus software is used to simulate the process with different mass ratios of coal to cotton stalk and for optimization: process efficiencies, net power generation and H2 production etc. are considered while environmental hazard emissions are optimized to acceptance level. With the addition of cotton stalk in feed, process efficiencies started to decline along with the net power production. But for H2 production, it gave positive result at start but after 40% cotton stalk addition, H2 production also started to decline. It also affects negatively on environmental hazard emissions and mass of emissions/ net power production increases linearly with the addition of cotton stalk in feed mixture. In summation with the addition of cotton stalk, overall affects seemed to negative. But the effect is more negative after 40% cotton stalk addition so it is concluded that to get maximum process efficiencies and high production less amount of cotton stalk addition in feed is preferable and the maximum level of addition is estimated to 40%. Gasification temperature should keep lower around 1140 °C and prefer technique for studied feed in IGCC is fluidized bed (ash in dry form) rather than ash slagging gasifier

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The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

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The use of intensity-modulated radiotherapy (IMRT) has increased extensively in the modern radiotherapy (RT) treatments over the past two decades. Radiation dose distributions can be delivered with higher conformality with IMRT when compared to the conventional 3D-conformal radiotherapy (3D-CRT). Higher conformality and target coverage increases the probability of tumour control and decreases the normal tissue complications. The primary goal of this work is to improve and evaluate the accuracy, efficiency and delivery techniques of RT treatments by using IMRT. This study evaluated the dosimetric limitations and possibilities of IMRT in small (treatments of head-and-neck, prostate and lung cancer) and large volumes (primitive neuroectodermal tumours). The dose coverage of target volumes and the sparing of critical organs were increased with IMRT when compared to 3D-CRT. The developed split field IMRT technique was found to be safe and accurate method in craniospinal irradiations. By using IMRT in simultaneous integrated boosting of biologically defined target volumes of localized prostate cancer high doses were achievable with only small increase in the treatment complexity. Biological plan optimization increased the probability of uncomplicated control on average by 28% when compared to standard IMRT delivery. Unfortunately IMRT carries also some drawbacks. In IMRT the beam modulation is realized by splitting a large radiation field to small apertures. The smaller the beam apertures are the larger the rebuild-up and rebuild-down effects are at the tissue interfaces. The limitations to use IMRT with small apertures in the treatments of small lung tumours were investigated with dosimetric film measurements. The results confirmed that the peripheral doses of the small lung tumours were decreased as the effective field size was decreased. The studied calculation algorithms were not able to model the dose deficiency of the tumours accurately. The use of small sliding window apertures of 2 mm and 4 mm decreased the tumour peripheral dose by 6% when compared to 3D-CRT treatment plan. A direct aperture based optimization (DABO) technique was examined as a solution to decrease the treatment complexity. The DABO IMRT technique was able to achieve treatment plans equivalent with the conventional IMRT fluence based optimization techniques in the concave head-and-neck target volumes. With DABO the effective field sizes were increased and the number of MUs was reduced with a factor of two. The optimality of a treatment plan and the therapeutic ratio can be further enhanced by using dose painting based on regional radiosensitivities imaged with functional imaging methods.