Computational Analysis and Optimization of Real Gas Flow In Small Centrifugal Compressors

Small centrifugal compressors are more and more widely used in many industrialsystems because of their higher efficiency and better off-design performance comparing to piston and scroll compressors as while as higher work coefficient perstage than in axial compressors. Higher efficiency is always the aim of the designer of compressors. In the present work, the influence of four partsof a small centrifugal compressor that compresses heavy molecular weight real gas has been investigated in order to achieve higher efficiency. Two parts concern the impeller: tip clearance and the circumferential position of the splitter blade. The other two parts concern the diffuser: the pinch shape and vane shape. Computational fluid dynamics is applied in this study. The Reynolds averaged Navier-Stokes flow solver Finflo is used. The quasi-steady approach is utilized. Chien's k-e turbulence model is used to model the turbulence. A new practical real gas model is presented in this study. The real gas model is easily generated, accuracy controllable and fairly fast. The numerical results and measurements show good agreement. The influence of tip clearance on the performance of a small compressor is obvious. The pressure ratio and efficiency are decreased as the size of tip clearance is increased, while the total enthalpy rise keeps almost constant. The decrement of the pressure ratio and efficiency is larger at higher mass flow rates and smaller at lower mass flow rates. The flow angles at the inlet and outlet of the impeller are increased as the size of tip clearance is increased. The results of the detailed flow field show that leakingflow is the main reason for the performance drop. The secondary flow region becomes larger as the size of tip clearance is increased and the area of the main flow is compressed. The flow uniformity is then decreased. A detailed study shows that the leaking flow rate is higher near the exit of the impeller than that near the inlet of the impeller. Based on this phenomenon, a new partiallyshrouded impeller is used. The impeller is shrouded near the exit of the impeller. The results show that the flow field near the exit of the impeller is greatly changed by the partially shrouded impeller, and better performance is achievedthan with the unshrouded impeller. The loading distribution on the impeller blade and the flow fields in the impeller is changed by moving the splitter of the impeller in circumferential direction. Moving the splitter slightly to the suction side of the long blade can improve the performance of the compressor. The total enthalpy rise is reduced if only the leading edge of the splitter ismoved to the suction side of the long blade. The performance of the compressor is decreased if the blade is bended from the radius direction at the leading edge of the splitter. The total pressure rise and the enthalpy rise of thecompressor are increased if pinch is used at the diffuser inlet. Among the fivedifferent pinch shape configurations, at design and lower mass flow rates the efficiency of a straight line pinch is the highest, while at higher mass flow rate, the efficiency of a concave pinch is the highest. The sharp corner of the pinch is the main reason for the decrease of efficiency and should be avoided. The variation of the flow angles entering the diffuser in spanwise direction is decreased if pinch is applied. A three-dimensional low solidity twisted vaned diffuser is designed to match the flow angles entering the diffuser. The numerical results show that the pressure recovery in the twisted diffuser is higher than in a conventional low solidity vaned diffuser, which also leads to higher efficiency of the twisted diffuser. Investigation of the detailed flow fields shows that the separation at lower mass flow rate in the twisted diffuser is later than in the conventional low solidity vaned diffuser, which leads to a possible wider flow range of the twisted diffuser.

MCMC Analysis for Optimization of Stochastic Models

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.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Stability Analysis in Multicriteria Discrete Portfolio Optimization.

Almost every problem of design, planning and management in the technical and organizational systems has several conflicting goals or interests. Nowadays, multicriteria decision models represent a rapidly developing area of operation research. While solving practical optimization problems, it is necessary to take into account various kinds of uncertainty due to lack of data, inadequacy of mathematical models to real-time processes, calculation errors, etc. In practice, this uncertainty usually leads to undesirable outcomes where the solutions are very sensitive to any changes in the input parameters. An example is the investment managing. Stability analysis of multicriteria discrete optimization problems investigates how the found solutions behave in response to changes in the initial data (input parameters). This thesis is devoted to the stability analysis in the problem of selecting investment project portfolios, which are optimized by considering different types of risk and efficiency of the investment projects. The stability analysis is carried out in two approaches: qualitative and quantitative. The qualitative approach describes the behavior of solutions in conditions with small perturbations in the initial data. The stability of solutions is defined in terms of existence a neighborhood in the initial data space. Any perturbed problem from this neighborhood has stability with respect to the set of efficient solutions of the initial problem. The other approach in the stability analysis studies quantitative measures such as stability radius. This approach gives information about the limits of perturbations in the input parameters, which do not lead to changes in the set of efficient solutions. In present thesis several results were obtained including attainable bounds for the stability radii of Pareto optimal and lexicographically optimal portfolios of the investment problem with Savage's, Wald's criteria and criteria of extreme optimism. In addition, special classes of the problem when the stability radii are expressed by the formulae were indicated. Investigations were completed using different combinations of Chebyshev's, Manhattan and Hölder's metrics, which allowed monitoring input parameters perturbations differently.

Use of field measurements in fatigue analysis of forestry cranes

Tässä työssä on esitetty väsyttävän kuormituksen mittaamiseen ja mittausdatan jälkikäsittelyyn sekä väsymismitoitukseen liittyviä menetelmiä. Menetelmien sovelluskohteena oli metsäkoneen kuormain, joka on väsyttävästi kuormitettu hitsattu rakenne. Teoriaosassa on kuvattu väsymisilmiötä ja väsymismitoitusmenetelmiä sekä kuormitusten tunnistamiseen ja mittausten jälkikäsittelyyn liittyviä menetelmiä. Yleisimmin käytettyjen väsymismitoitusmenetelmien rinnalle on esitetty luotettavuuteen perustuvaa väsymismitoitusmenetelmää. Kuormainten suunnittelussa on keveys- j a kestoikävaatimusten takia erityisen suuri merkitys väsymisen huomioimisella. Rakenteille on ominaista tietyt toiminnan kannalta välttämättömät hitsatut yksityiskohdat, jotka usein määräävät koko rakenteen kestoiän. Koska nämä ongelmakohdat pystytään useimmiten tunnistamaan jo suunnitteluvaiheessa, voidaan yksityiskohtien muotoilulla usein parantaa huomattavasti koko rakenteen kestoikää. Näiden yksityiskohtien optimointi on osittain mahdollista toteuttaa ilman kuormituskertymätietoa, mutta useimmiten kuormitusten tunnistaminen on edellytys parhaan ratkaisun löytymiselle. Tällöin toistaiseksi paras keino todellisen väsyttävän kuormituksen tunnistamiseksi on pitkäaikaiset kenttämittaukset. Kenttämittauksilla selvitetään rakenteeseen kohdistuvat kuormitukset venymäliuskojen avulla. Kuormitusten tunnistamisella on erityisen suuri merkitys kun halutaan määrittää rakenteen kestoikä. Väsyminen ja väsyttävä kuormitus ovat kuitenkin tilastollisia muuttujia j a yksittäiselle rakenteelle ei ole mahdollista määrittää tarkkaa k estoikää. Tilastollisia menetelmiä käyttäen on kuitenkin mahdollista määrittää rakenteen vaurioitumisriski. Laskettaessa vaurioitumisriskiä suurelle määrälle yksittäisiä rakenteita voidaan muodostaa tarkkojakin ennusteita mahdollisten vaurioiden lukumäärästä. Tällöin kuormituskertymätiedosta voi olla tavanomaisen suunnittelun lisäksi laajempaa hyötyä esimerkiksi takuukäsittelyssä. Tässä työssä on sovellettu esitettyjä teorioita käytännössä metsäkoneen harvesterin puomiston väsymistarkasteluun. Kyseisen rakenteen kuormituksia mitattiin kahden viikon aikana yhteensä 35 tuntia, jonka perusteella laskettiin väsyttävän kuormituksen tilastollinen jakauma esimerkkitapaukselle. Mittauksen perusteella ei voitu tehdä kuitenkaan johtopäätöksiä tuotteen koko elinkaaren kuormituksista eikä muiden samanlaisten tuotteiden kuormituksista, koska mitattu otos oli suhteellisen lyhyt ja rajoittui vain yhteen käyttäjään ja muutamaan käyttökohteeseen. Menetelmien testaamiseksi kyseinen otos oli kuitenkin riittävä. Kuormituskertymätietoa käytettiin hyväksi myös laatumääritysten muodostamisessaesimerkkitapaukselle. Murtumismekaniikkaan perustuvalla menetelmällä arvioitiinharvesteripilarin valun mahdollisten valuvirheiden suurin sallittu koko. Luotettavuuteen pohjautuvan mitoitusmenettelyn tarve näyttää olevanlisääntymässä, joten pitkäaikaisten kenttämittausten tehokas hyödyntäminen tulee olemaan keskeinen osa väsymismitoitusta lähitulevaisuudessa. Menetelmiä olisi mahdollista tehostaa yhdistämällä kuormituskertymään erilaisia kuormitusten suhteen riippuvia tunnettuja suureita kuten käsiteltävän puun halkaisija. Todellisettuotekohtaiset tilastolliset jakaumat kuormituksista voitaisiin muodostaa mahdollisesti tehokkaammin, jos esimerkiksi kuormitusten riippuvuus metsätyypistä pystyttäisiin ensin määrittämään.

Optimization of the procedure for removing iron deposits on ceramic filter media

In this thesis, cleaning of ceramic filter media was studied. Mechanisms of fouling and dissolution of iron compounds, as well as methods for cleaning ceramic membranes fouled by iron deposits were studied in the literature part. Cleaning agents and different methods were closer examined in the experimental part of the thesis. Pyrite is found in the geologic strata. It is oxidized to form ferrous ions Fe(II) and ferric ions Fe(III). Fe(III) is further oxidized in the hydrolysis to form ferric hydroxide. Hematite and goethite, for instance, are naturally occurring iron oxidesand hydroxides. In contact with filter media, they can cause severe fouling, which common cleaning techniques competent enough to remove. Mechanisms for the dissolution of iron oxides include the ligand-promoted pathway and the proton-promoted pathway. The dissolution can also be reductive or non-reductive. The most efficient mechanism is the ligand-promoted reductive mechanism that comprises two stages: the induction period and the autocatalytic dissolution.Reducing agents(such as hydroquinone and hydroxylamine hydrochloride), chelating agents (such as EDTA) and organic acids are used for the removal of iron compounds. Oxalic acid is the most effective known cleaning agent for iron deposits. Since formulations are often more effective than organic acids, reducing agents or chelating agents alone, the citrate¿bicarbonate¿dithionite system among others is well studied in the literature. The cleaning is also enhanced with ultrasound and backpulsing.In the experimental part, oxalic acid and nitric acid were studied alone andin combinations. Also citric acid and ascorbic acid among other chemicals were tested. Soaking experiments, experiments with ultrasound and experiments for alternative methods to apply the cleaning solution on the filter samples were carried out. Permeability and ISO Brightness measurements were performed to examine the influence of the cleaning methods on the samples. Inductively coupled plasma optical emission spectroscopy (ICP-OES) analysis of the solutions was carried out to determine the dissolved metals.

Direct torque control of permanent magnet synchronous machines - analysis and implementation

Thedirect torque control (DTC) has become an accepted vector control method besidethe current vector control. The DTC was first applied to asynchronous machines,and has later been applied also to synchronous machines. This thesis analyses the application of the DTC to permanent magnet synchronous machines (PMSM). In order to take the full advantage of the DTC, the PMSM has to be properly dimensioned. Therefore the effect of the motor parameters is analysed taking the control principle into account. Based on the analysis, a parameter selection procedure is presented. The analysis and the selection procedure utilize nonlinear optimization methods. The key element of a direct torque controlled drive is the estimation of the stator flux linkage. Different estimation methods - a combination of current and voltage models and improved integration methods - are analysed. The effect of an incorrect measured rotor angle in the current model is analysed andan error detection and compensation method is presented. The dynamic performance of an earlier presented sensorless flux estimation method is made better by improving the dynamic performance of the low-pass filter used and by adapting the correction of the flux linkage to torque changes. A method for the estimation ofthe initial angle of the rotor is presented. The method is based on measuring the inductance of the machine in several directions and fitting the measurements into a model. The model is nonlinear with respect to the rotor angle and therefore a nonlinear least squares optimization method is needed in the procedure. A commonly used current vector control scheme is the minimum current control. In the DTC the stator flux linkage reference is usually kept constant. Achieving the minimum current requires the control of the reference. An on-line method to perform the minimization of the current by controlling the stator flux linkage reference is presented. Also, the control of the reference above the base speed is considered. A new estimation flux linkage is introduced for the estimation of the parameters of the machine model. In order to utilize the flux linkage estimates in off-line parameter estimation, the integration methods are improved. An adaptive correction is used in the same way as in the estimation of the controller stator flux linkage. The presented parameter estimation methods are then used in aself-commissioning scheme. The proposed methods are tested with a laboratory drive, which consists of a commercial inverter hardware with a modified software and several prototype PMSMs.

Railway Wagon Market Analysis and New Multi-Purpose Wagon Solution for Freight Transports - Finnish Manufacturing Perspective

Rautateillä käytettävät tavaravaunut ovat vanhenemassa hyvin nopeasti; tämä koskee niin Venäjää, Suomea, Ruotsia kuin laajemminkin Eurooppaa. Venäjällä ja Euroopassa on käytössä runsaasti vaunuja, jotka ovat jo ylittäneet niille suositeltavan käyttöiän. Silti niitä käytetään kuljetuksissa, kun näitä korvaavia uusia vaunuja ei ole tarpeeksi saatavilla. Uusimmat vaunut ovat yleensä vaunuja vuokraavien yritysten tai uusien rautatieoperaattorien hankkimia - tämä koskee erityisesti Venäjää, jossa vaunuvuokraus on noussut erittäin suosituksi vaihtoehdoksi. Ennusteissa kerrotaan vaunupulan kasvavan ainakin vuoteen 2010 saakka. Jos rautateiden suosio rahtikuljetusmuotona kasvaa, niin voimistuva vaunukysyntä jatkuu huomattavan paljon pidemmän aikaa. Euroopan ja Venäjän vaunukannan tilanne näkyy myös sitä palvelevan konepajateollisuuden ongelmina - yleisesti ottaen alan eurooppalaiset yritykset ovat heikosti kannattavia ja niiden liikevaihto ei juuri kasva, venäläiset ja ukrainalaiset yritykset ovat olleet samassa tilanteessa, joskin aivan viime vuosina tilanne on osassa kääntynyt paremmaksi. Kun näiden maanosien yritysten liikevaihtoa, voittoa ja omistaja-arvoa verrataan yhdysvaltalaisiin kilpailijoihin, huomataan että jälkimmäisten suoriutuminen on huomattavan paljon parempaa, ja näillä yrityksillä on myös kyky maksaa osinkoja omistajilleen. Tutkimuksen tarkoituksena oli kehittää uuden tyyppinen kuljetusvaunu Suomen, Venäjän sekä mahdollisesti myös Kiinan väliseen liikenteeseen. Vaunutyypin tarkoituksena olisi kyetä toimimaan monikäyttöisenä, niin raaka-aineiden kuin konttienkin kuljetuksessa, tasapainottaen kuljetusmuotojen aiheuttamaa kuljetuspaino-ongelmaa. Kehitystyön pohjana käytimme yli 1000 venäläisen vaunutyypin tietokantaa, josta valitsimme Data Envelopment Analysis -menetelmällä soveliaimmat vaunut kontinkuljetukseen (lähemmin tarkastelimme n. 40 vaunutyyppiä), jättäen mahdollisimman vähän tyhjää tilaa junaan, mutta silti kyeten kantamaan valitun konttilastin. Kun kantokykyongelmia venäläisissä vaunuissa ei useinkaan ole, on vertailu tehtävissä tavarajunan pituuden ja kokonaispainon perusteella. Simuloituamme yhdistettyihin kuljetuksiin soveliasta vaunutyyppiä käytännössä löytyvässä kuljetusverkostossa (esim. raakapuuta Suomeen tai Kiinaan ja kontteja takaisin Venäjän suuntaan), huomasimme lyhemmän vaunupituuden sisältävän kustannusetua, erityisesti raakaainekuljetuksissa, mutta myös rajanylityspaikkojen mahdollisesti vähentyessä. Lyhempi vaunutyyppi on myös joustavampi erilaisten konttipituuksien suhteen (40 jalan kontin käyttö on yleistynyt viime vuosina). Työn lopuksi ehdotamme uuden vaunutyypin tuotantotavaksi verkostomaista lähestymistapaa, jossa osa vaunusta tehtäisiin Suomessa ja osa Venäjällä ja/tai Ukrainassa. Vaunutyypin tulisi olla rekisteröity Venäjälle, sillä silloin sitä voi käyttää Suomen ja Venäjän, kuten myös soveltuvin osin Venäjän ja Kiinan välisessä liikenteessä.

Analyzing Carbon Trade Permits in Optimization Framework

The threats caused by global warming motivate different stake holders to deal with and control them. This Master's thesis focuses on analyzing carbon trade permits in optimization framework. The studied model determines optimal emission and uncertainty levels which minimize the total cost. Research questions are formulated and answered by using different optimization tools. The model is developed and calibrated by using available consistent data in the area of carbon emission technology and control. Data and some basic modeling assumptions were extracted from reports and existing literatures. The data collected from the countries in the Kyoto treaty are used to estimate the cost functions. Theory and methods of constrained optimization are briefly presented. A two-level optimization problem (individual and between the parties) is analyzed by using several optimization methods. The combined cost optimization between the parties leads into multivariate model and calls for advanced techniques. Lagrangian, Sequential Quadratic Programming and Differential Evolution (DE) algorithm are referred to. The role of inherent measurement uncertainty in the monitoring of emissions is discussed. We briefly investigate an approach where emission uncertainty would be described in stochastic framework. MATLAB software has been used to provide visualizations including the relationship between decision variables and objective function values. Interpretations in the context of carbon trading were briefly presented. Suggestions for future work are given in stochastic modeling, emission trading and coupled analysis of energy prices and carbon permits.

Sampling in chemical analysis

The uncertainty of any analytical determination depends on analysis and sampling. Uncertainty arising from sampling is usually not controlled and methods for its evaluation are still little known. Pierre Gy’s sampling theory is currently the most complete theory about samplingwhich also takes the design of the sampling equipment into account. Guides dealing with the practical issues of sampling also exist, published by international organizations such as EURACHEM, IUPAC (International Union of Pure and Applied Chemistry) and ISO (International Organization for Standardization). In this work Gy’s sampling theory was applied to several cases, including the analysis of chromite concentration estimated on SEM (Scanning Electron Microscope) images and estimation of the total uncertainty of a drug dissolution procedure. The results clearly show that Gy’s sampling theory can be utilized in both of the above-mentioned cases and that the uncertainties achieved are reliable. Variographic experiments introduced in Gy’s sampling theory are beneficially applied in analyzing the uncertainty of auto-correlated data sets such as industrial process data and environmental discharges. The periodic behaviour of these kinds of processes can be observed by variographic analysis as well as with fast Fourier transformation and auto-correlation functions. With variographic analysis, the uncertainties are estimated as a function of the sampling interval. This is advantageous when environmental data or process data are analyzed as it can be easily estimated how the sampling interval is affecting the overall uncertainty. If the sampling frequency is too high, unnecessary resources will be used. On the other hand, if a frequency is too low, the uncertainty of the determination may be unacceptably high. Variographic methods can also be utilized to estimate the uncertainty of spectral data produced by modern instruments. Since spectral data are multivariate, methods such as Principal Component Analysis (PCA) are needed when the data are analyzed. Optimization of a sampling plan increases the reliability of the analytical process which might at the end have beneficial effects on the economics of chemical analysis,

Optimization of wind blade design including its energetic characteristics

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.

Optimization as a method of search engine marketing

This study is dedicated to search engine marketing (SEM). It aims for developing a business model of SEM firms and to provide explicit research of trustworthy practices of virtual marketing companies. Optimization is a general term that represents a variety of techniques and methods of the web pages promotion. The research addresses optimization as a business activity, and it explains its role for the online marketing. Additionally, it highlights issues of unethical techniques utilization by marketers which created relatively negative attitude to them on the Internet environment. Literature insight combines in the one place both technical and economical scientific findings in order to highlight technological and business attributes incorporated in SEM activities. Empirical data regarding search marketers was collected via e-mail questionnaires. 4 representatives of SEM companies were engaged in this study to accomplish the business model design. Additionally, the fifth respondent was a representative of the search engine portal, who provided insight on relations between search engines and marketers. Obtained information of the respondents was processed qualitatively. Movement of commercial organizations to the online market increases demand on promotional programs. SEM is the largest part of online marketing, and it is a prerogative of search engines portals. However, skilled users, or marketers, are able to implement long-term marketing programs by utilizing web page optimization techniques, key word consultancy or content optimization to increase web site visibility to search engines and, therefore, user’s attention to the customer pages. SEM firms are related to small knowledge-intensive businesses. On the basis of data analysis the business model was constructed. The SEM model includes generalized constructs, although they represent a wider amount of operational aspects. Constructing blocks of the model includes fundamental parts of SEM commercial activity: value creation, customer, infrastructure and financial segments. Also, approaches were provided on company’s differentiation and competitive advantages evaluation. It is assumed that search marketers should apply further attempts to differentiate own business out of the large number of similar service providing companies. Findings indicate that SEM companies are interested in the increasing their trustworthiness and the reputation building. Future of the search marketing is directly depending on search engines development.

Qualitative Characteristics and Quantitative Measures of Solution's Reliability in Discrete Optimization: Traditional Analytical Approaches, Innovative Computational Methods and Applicability

The purpose of this thesis is twofold. The first and major part is devoted to sensitivity analysis of various discrete optimization problems while the second part addresses methods applied for calculating measures of solution stability and solving multicriteria discrete optimization problems. Despite numerous approaches to stability analysis of discrete optimization problems two major directions can be single out: quantitative and qualitative. Qualitative sensitivity analysis is conducted for multicriteria discrete optimization problems with minisum, minimax and minimin partial criteria. The main results obtained here are necessary and sufficient conditions for different stability types of optimal solutions (or a set of optimal solutions) of the considered problems. Within the framework of quantitative direction various measures of solution stability are investigated. A formula for a quantitative characteristic called stability radius is obtained for the generalized equilibrium situation invariant to changes of game parameters in the case of the H¨older metric. Quality of the problem solution can also be described in terms of robustness analysis. In this work the concepts of accuracy and robustness tolerances are presented for a strategic game with a finite number of players where initial coefficients (costs) of linear payoff functions are subject to perturbations. Investigation of stability radius also aims to devise methods for its calculation. A new metaheuristic approach is derived for calculation of stability radius of an optimal solution to the shortest path problem. The main advantage of the developed method is that it can be potentially applicable for calculating stability radii of NP-hard problems. The last chapter of the thesis focuses on deriving innovative methods based on interactive optimization approach for solving multicriteria combinatorial optimization problems. The key idea of the proposed approach is to utilize a parameterized achievement scalarizing function for solution calculation and to direct interactive procedure by changing weighting coefficients of this function. In order to illustrate the introduced ideas a decision making process is simulated for three objective median location problem. The concepts, models, and ideas collected and analyzed in this thesis create a good and relevant grounds for developing more complicated and integrated models of postoptimal analysis and solving the most computationally challenging problems related to it.

Accuracy Analysis of Frequency Converter Estimates in Diagnostic Applications

Transportation of fluids is one of the most common and energy intensive processes in the industrial and HVAC sectors. Pumping systems are frequently subject to engineering malpractice when dimensioned, which can lead to poor operational efficiency. Moreover, pump monitoring requires dedicated measuring equipment, which imply costly investments. Inefficient pump operation and improper maintenance can increase energy costs substantially and even lead to pump failure. A centrifugal pump is commonly driven by an induction motor. Driving the induction motor with a frequency converter can diminish energy consumption in pump drives and provide better control of a process. In addition, induction machine signals can also be estimated by modern frequency converters, dispensing with the use of sensors. If the estimates are accurate enough, a pump can be modelled and integrated into the frequency converter control scheme. This can open the possibility of joint motor and pump monitoring and diagnostics, thereby allowing the detection of reliability-reducing operating states that can lead to additional maintenance costs. The goal of this work is to study the accuracy of rotational speed, torque and shaft power estimates calculated by a frequency converter. Laboratory tests were performed in order to observe estimate behaviour in both steady-state and transient operation. An induction machine driven by a vector-controlled frequency converter, coupled with another induction machine acting as load was used in the tests. The estimated quantities were obtained through the frequency converter’s Trend Recorder software. A high-precision, HBM T12 torque-speed transducer was used to measure the actual values of the aforementioned variables. The effect of the flux optimization energy saving feature on the estimate quality was also studied. A processing function was developed in MATLAB for comparison of the obtained data. The obtained results confirm the suitability of this particular converter to provide accurate enough estimates for pumping applications.

Search and Paper SKU Analysis of Recipes Meeting EUPS Standard

The theoretical research of the study concentrated on finding theoretical frameworks to optimize the amount of needed stock keeping units (SKUs) in manufacturing industry. The goal was to find ways for a company to acquire an optimal collection of stock keeping units needed for manufacturing needed amount of end products. The research follows constructive research approach leaning towards practical problem solving. In the empirical part of this study, a recipe search tool was developed to an existing database used in the target company. The purpose of the tools was to find all the recipes meeting the EUPS performance standard and put the recipes in a ranking order using the data available in the database. The ranking of the recipes was formed from the combination of the performance measures and price of the recipes. In addition, the tool researched what kind of paper SKUs were needed to manufacture the best performing recipes. The tool developed during this process meets the requirements. It eases and makes it much faster to search for all the recipes meeting the EUPS standard. Furthermore, many future development possibilities for the tool were discovered while writing the thesis.