Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.

A modified nominal stress method for fatigue assessment of steel plates with thermally cut edges

Thermal cutting methods, are commonly used in the manufacture of metal parts. Thermal cutting processes separate materials by using heat. The process can be done with or without a stream of cutting oxygen. Common processes are Oxygen, plasma and laser cutting. It depends on the application and material which cutting method is used. Numerically-controlled thermal cutting is a cost-effective way of prefabricating components. One design aim is to minimize the number of work steps in order to increase competitiveness. This has resulted in the holes and openings in plate parts manufactured today being made using thermal cutting methods. This is a problem from the fatigue life perspective because there is local detail in the as-welded state that causes a rise in stress in a local area of the plate. In a case where the static utilization of a net section is full used, the calculated linear local stresses and stress ranges are often over 2 times the material yield strength. The shakedown criteria are exceeded. Fatigue life assessment of flame-cut details is commonly based on the nominal stress method. For welded details, design standards and instructions provide more accurate and flexible methods, e.g. a hot-spot method, but these methods are not universally applied to flame cut edges. Some of the fatigue tests of flame cut edges in the laboratory indicated that fatigue life estimations based on the standard nominal stress method can give quite a conservative fatigue life estimate in cases where a high notch factor was present. This is an undesirable phenomenon and it limits the potential for minimizing structure size and total costs. A new calculation method is introduced to improve the accuracy of the theoretical fatigue life prediction method of a flame cut edge with a high stress concentration factor. Simple equations were derived by using laboratory fatigue test results, which are published in this work. The proposed method is called the modified FAT method (FATmod). The method takes into account the residual stress state, surface quality, material strength class and true stress ratio in the critical place.

Lossless compression of hyperspectral images

Technological progress has made a huge amount of data available at increasing spatial and spectral resolutions. Therefore, the compression of hyperspectral data is an area of active research. In somefields, the original quality of a hyperspectral image cannot be compromised andin these cases, lossless compression is mandatory. The main goal of this thesisis to provide improved methods for the lossless compression of hyperspectral images. Both prediction- and transform-based methods are studied. Two kinds of prediction based methods are being studied. In the first method the spectra of a hyperspectral image are first clustered and and an optimized linear predictor is calculated for each cluster. In the second prediction method linear prediction coefficients are not fixed but are recalculated for each pixel. A parallel implementation of the above-mentioned linear prediction method is also presented. Also,two transform-based methods are being presented. Vector Quantization (VQ) was used together with a new coding of the residual image. In addition we have developed a new back end for a compression method utilizing Principal Component Analysis (PCA) and Integer Wavelet Transform (IWT). The performance of the compressionmethods are compared to that of other compression methods. The results show that the proposed linear prediction methods outperform the previous methods. In addition, a novel fast exact nearest-neighbor search method is developed. The search method is used to speed up the Linde-Buzo-Gray (LBG) clustering method.

Predicting diffusion of innovations with self-organisation and machine learning

The main subject of this master's thesis was predicting diffusion of innovations. The prediction was done in a special case: product has been available in some countries, and based on its diffusion in those countries the prediction is done for other countries. The prediction was based on finding similar countries with Self-Organizing Map~(SOM), using parameters of countries. Parameters included various economical and social key figures. SOM was optimised for different products using two different methods: (a) by adding diffusion information of products to the country parameters, and (b) by weighting the country parameters based on their importance for the diffusion of different products. A novel method using Differential Evolution (DE) was developed to solve the latter, highly non-linear optimisation problem. Results were fairly good. The prediction method seems to be on a solid theoretical foundation. The results based on country data were good. Instead, optimisation for different products did not generally offer clear benefit, but in some cases the improvement was clearly noticeable. The weights found for the parameters of the countries with the developed SOM optimisation method were interesting, and most of them could be explained by properties of the products.

Ydinvoimalaitoksen höyryturbiinin suorituskyvyn laskenta

Diplomityön tavoitteena on selvittää Loviisan ydinvoimalaitoksen höyryturbiinin hyötysuhteen parantamismahdollisuuksia. Työn kuvaan liittyvät oleellisesti höyryturbiinin siipivyöhykkeiden nopeuskolmioiden sekä hyötysuhteiden laskenta. Höyryturbiinien kehityskaarta sekä turbiinin häviökerrointen laskentayhtälöitä on esitetty useasta eri lähteestä ja vuosikymmeniltä. Työssä selvitettiin uusimpia ydinvoimalaitosten kostea höyryturbiinien suunnitteluperusteita lukuisista eri lähteistä. Kaikkien lähteiden mukaan kostean höyryn alueella tapahtuvaa paisuntaa on haasteellista mallintaa. Työssä on esitelty artikkeleissa tulleita eri näkökulmia höyryturbiinien suorituskyvyn parantamiseksi, sekä rakenteellisia että laskennallisia. Työssä esitellään monia turbiinin virtauksen ja suorituskyvyn laskentamenetelmiä. Esimerkiksi Baumannin säännön laskenta on yksinkertainen tapa käsitellä turbiinin suorituskykyä kostean höyryn alueella. Keskeisimpiä tehtyjä havaintoja oli se, että korkeapaineturbiinin ensimmäisestä vaiheesta löytyi mahdollista parannuspotentiaalia Loviisaan ydinvoimalaitoksen tehon lisäämiseksi. Ensimmäisessä vaiheessa on oletettu siipien olevan Laval –tyyppisiä, mutta käytännössä näin ei ole. Korkeapaineturbiinin nykyisen turbosuuttimen toimintaa voitaisiin tehostaa. Lisäksi Loviisan matalapaineturbiinin viimeisen siipivaiheen jälkeen aiheutuu suuret ulosvirtaushäviöt. Osa suurinopeuksisen virtauksen energiasta pystyttäisiin kuitenkin hyödyntämään vielä ulosvirtauskanavassa olevalla diffuusorilla.

Very High Energy Gamma-Rays emitting BL LAC's Population Study

Context: BL Lacs are the most numerous extragalactic objects which are detected in Very High Energy (VHE) gamma-rays band. They are a subclass of blazars. Large flux variability amplitude, sometimes happens in very short time scale, is a common characteristic of them. Significant optical polarization is another main characteristics of BL Lacs. BL Lacs' spectra have a continuous and featureless Spectral Energy Distribution (SED) which have two peaks. Among 1442 BL Lacs in the Roma-BZB catalogue, only 51 are detected in VHE gamma-rays band. BL Lacs are most numerous (more than 50% of 514 objects) objects among the sources that are detected above 10 GeV by FERMI-LAT. Therefore, many BL Lacs are expected to be discovered in VHE gamma-rays band. However, due to the limitation on current and near future technology of Imaging Air Cherenkov Telescope, astronomers are forced to predict whether an object emits VHE gamma-rays or not. Some VHE gamma-ray prediction methods are already introduced but still are not confirmed. Cross band correlations are the building blocks of introducing VHE gamma-rays prediction method. Aims: We will attempt to investigate cross band correlations between flux energy density, luminosity and spectral index of the sample. Also, we will check whether recently discovered MAGIC J2001+435 is a typical BL Lac. Methods: We select a sample of 42 TeV BL Lacs and collect 20 of their properties within five energy bands from literature and Tuorla blazar monitoring program database. All of the data are synchronized to be comparable to each other. Finally, we choose 55 pair of datasets for cross band correlations finding and investigating whether there is any correlation between each pair. For MAGIC J2001+435 we analyze the publicly available SWIFT-XRT data, and use the still unpublished VHE gamma-rays data from MAGIC collaboration. The results are compared to the other sources of the sample. Results: Low state luminosity of multiple detected VHE gamma-rays is strongly correlated luminosities in all other bands. However, the high state does not show such strong correlations. VHE gamma-rays single detected sources have similar behaviour to the low state of multiple detected ones. Finally, MAGIC J2001+435 is a typical TeV BL Lac. However, for some of the properties this source is located at the edge of the whole sample (e.g. in terms of X-rays flux). Keywords: BL Lac(s), Population study, Correlations finding, Multi wavelengths analysis, VHE gamma-rays, gamma-rays, X-rays, Optical, Radio

Development of a Testing Method for Convertibility of Paperboard

Työssä tutkittiin muovattujen kartonkivuokien sekä muovattujen kartonkinäytteiden rinnastettavuutta. Puristusvaiheen prosessiolosuhteiden miellettiin vaikuttavan eniten multidimensionaliseen muodonmuutokseen. Multidimensionaalista muodonmuutosta simuloitiin uudella muovaamiseen soveltuvalla muovauslaitteella. Kirjallisuusosassa keskeisiä teemoja ovat kartongin muovaus sekä kuitupohjaisen materiaalin reologinen käyttäytyminen. Kirjallisuusosassa esitellään lisäksi yksi tekninen sovellus, jonka avulla kyetään ennustamaan kuitumateriaalin muovautuvuutta sekä mittaamaan tapahtunutta muodonmuutosta. Prosessiparametrien teoreettista vaikutustakuituihin tarkastellaan myös kirjallisuusosassa. Kokeellisessa osassa toteutettiin kartonkivuokien valmistus puristamalla. Vastaavilla prosessiparametreilla muovattiin myös pienemmät testinäytteet. Perinteiset yksidimensionaliset deformaatiomittaukset toteutettiin lujuusominaisuuksien laboratoriomäärityksinä. Myös kitka, joka toimii tärkeänä muuttujana prässäysprosessissa, mitattiin laboratorio-olosuhteissa. Tämän työn tulokset osoittavat uuden kehitetyn muovausmenetelmän toimivuuden. Asema-voima kuvaajat ovat selkeitä sekä helposti luettavia. Tuloksissa havaittiin materiaalin muovauspotentiaalin sekä asema-voima kuvaajan välillä vallitseva yhteys. Erittäin merkittävä huomio oli myös, että muovipäällystetyllä kartongilla oli yhteys päällystämättömän kartongin asema-voima kuvaajaan. Tämä tulos osoittaa, että muovipäällystetyn kartongin muovautuvuutta voi olla mahdollista ennustaa pohjakartongin muovautuvuustulosten perusteella. Perinteiset yksidimensionaliset laboratoriomittaukset eivät kykene antamaan riittävää informaatiota muovautuvuuden ennustamiseen. Tästä näkökulmasta on tärkeää että kartongin multidimensionalista muotoutuvuutta voidaankin tutkia kehitetyllä muovausmenetelmällä.

Characterization Method for Comminution Behavior of Limestone and Fuel Ash in a Circulating Fluidized Bed Boiler

Työn tavoite oli kehittää karakterisointimenetelmät kalkkikiven ja polttoaineen tuhkan jauhautumisen ennustamiselle kiertoleijukattilan tulipesässä. Kiintoainekäyttäytymisen karakterisoinnilla ja mallintamisella voidaan tarkentaa tulipesän lämmönsiirron ja tuhkajaon ennustamista. Osittain kokeelliset karakterisointimenetelmät perustuvat kalkkikiven jauhautumiseen laboratoriokokoluokan leijutetussa kvartsiputkireaktorissa ja tuhkan jauhatumiseen rotaatiomyllyssä. Karakterisointimenetelmät ottavat huomioon eri-laiset toimintaolosuhteet kaupallisen kokoluokan kiertoleijukattiloissa. Menetelmät kelpoistettiin kaupallisen kokoluokan kiertoleijukattiloista mitattujen ja fraktioittaisella kiintoainemallilla mallinnettujen taseiden avulla. Kelpoistamistaseiden vähäisyydestä huolimatta karakterisointimenetelmät arvioitiin virhetarkastelujen perusteella järkeviksi. Karakterisointimenetelmien kehittämistä ja tarkentamista tullaan jatkamaan.

Minimization of the experimental workload for the prediction of pollutants propagation in rivers. Mathematical modelling and knowledge re-use

The present thesis in focused on the minimization of experimental efforts for the prediction of pollutant propagation in rivers by mathematical modelling and knowledge re-use. Mathematical modelling is based on the well known advection-dispersion equation, while the knowledge re-use approach employs the methods of case based reasoning, graphical analysis and text mining. The thesis contribution to the pollutant transport research field consists of: (1) analytical and numerical models for pollutant transport prediction; (2) two novel techniques which enable the use of variable parameters along rivers in analytical models; (3) models for the estimation of pollutant transport characteristic parameters (velocity, dispersion coefficient and nutrient transformation rates) as functions of water flow, channel characteristics and/or seasonality; (4) the graphical analysis method to be used for the identification of pollution sources along rivers; (5) a case based reasoning tool for the identification of crucial information related to the pollutant transport modelling; (6) and the application of a software tool for the reuse of information during pollutants transport modelling research. These support tools are applicable in the water quality research field and in practice as well, as they can be involved in multiple activities. The models are capable of predicting pollutant propagation along rivers in case of both ordinary pollution and accidents. They can also be applied for other similar rivers in modelling of pollutant transport in rivers with low availability of experimental data concerning concentration. This is because models for parameter estimation developed in the present thesis enable the calculation of transport characteristic parameters as functions of river hydraulic parameters and/or seasonality. The similarity between rivers is assessed using case based reasoning tools, and additional necessary information can be identified by using the software for the information reuse. Such systems represent support for users and open up possibilities for new modelling methods, monitoring facilities and for better river water quality management tools. They are useful also for the estimation of environmental impact of possible technological changes and can be applied in the pre-design stage or/and in the practical use of processes as well.

Bankruptcy prediction using fuzzy methods

In this thesis, a classi cation problem in predicting credit worthiness of a customer is tackled. This is done by proposing a reliable classi cation procedure on a given data set. The aim of this thesis is to design a model that gives the best classi cation accuracy to e ectively predict bankruptcy. FRPCA techniques proposed by Yang and Wang have been preferred since they are tolerant to certain type of noise in the data. These include FRPCA1, FRPCA2 and FRPCA3 from which the best method is chosen. Two di erent approaches are used at the classi cation stage: Similarity classi er and FKNN classi er. Algorithms are tested with Australian credit card screening data set. Results obtained indicate a mean classi cation accuracy of 83.22% using FRPCA1 with similarity classi- er. The FKNN approach yields a mean classi cation accuracy of 85.93% when used with FRPCA2, making it a better method for the suitable choices of the number of nearest neighbors and fuzziness parameters. Details on the calibration of the fuzziness parameter and other parameters associated with the similarity classi er are discussed.

Linear prediction in optical spectroscopy

A linear prediction procedure is one of the approved numerical methods of signal processing. In the field of optical spectroscopy it is used mainly for extrapolation known parts of an optical signal in order to obtain a longer one or deduce missing signal samples. The first is needed particularly when narrowing spectral lines for the purpose of spectral information extraction. In the present paper the coherent anti-Stokes Raman scattering (CARS) spectra were under investigation. The spectra were significantly distorted by the presence of nonlinear nonresonant background. In addition, line shapes were far from Gaussian/Lorentz profiles. To overcome these disadvantages the maximum entropy method (MEM) for phase spectrum retrieval was used. The obtained broad MEM spectra were further underwent the linear prediction analysis in order to be narrowed.

Warranty Prediction Using Weibull Simulation

The main objective of this master’s thesis is to examine if Weibull analysis is suitable method for warranty forecasting in the Case Company. The Case Company has used Reliasoft’s Weibull++ software, which is basing on the Weibull method, but the Company has noticed that the analysis has not given right results. This study was conducted making Weibull simulations in different profit centers of the Case Company and then comparing actual cost and forecasted cost. Simula-tions were made using different time frames and two methods for determining future deliveries. The first sub objective is to examine, which parameters of simulations will give the best result to each profit center. The second sub objective of this study is to create a simple control model for following forecasted costs and actual realized costs. The third sub objective is to document all Qlikview-parameters of profit centers. This study is a constructive research, and solutions for company’s problems are figured out in this master’s thesis. In the theory parts were introduced quality issues, for example; what is quality, quality costing and cost of poor quality. Quality is one of the major aspects in the Case Company, so understand-ing the link between quality and warranty forecasting is important. Warranty management was also introduced and other different tools for warranty forecasting. The Weibull method and its mathematical properties and reliability engineering were introduced. The main results of this master’s thesis are that the Weibull analysis forecasted too high costs, when calculating provision. Although, some forecasted values of profit centers were lower than actual values, the method works better for planning purposes. One of the reasons is that quality improving or alternatively quality decreasing is not showing in the results of the analysis in the short run. The other reason for too high values is that the products of the Case Company are com-plex and analyses were made in the profit center-level. The Weibull method was developed for standard products, but products of the Case Company consists of many complex components. According to the theory, this method was developed for homogeneous-data. So the most im-portant notification is that the analysis should be made in the product level, not the profit center level, when the data is more homogeneous.