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.

Success Factors of an Enterprise Resource Planning System

Työn tarkoituksena oli tutkia yrityksen eri yksiköiden toiminnaohjausjärjestelmiä sekä verrata niiden menestystekijöitä Adelakunin malliin tietojärjestelmien laatuulottuvuuksista. Siinä järjestelmän kokonaislaatu jaetaan liiketoiminnalliseen, tekniseen ja käyttäjän kokemaan laatuun. Tulosten perusteella oli myös tavoitteena kehittää kyseisen toiminnanojausjärjestelmän kehittämistä varten malli onnistumistekijöiden keskinäisestä riippuvuudesta. Tutkittavista järjestelmistä ja niiden käytöstä kerättiin tietoja käyttöönottoprojektien dokumentaatiosta, haastatteluin, kyselylomakkein ja järjestelmäanalyysein. Sekä loppukäyttäjät että yritysjohto olivat kyselyjen ja haastattelujen kohderyhmänä. Saatuja tietoja arvioitiin Adelakunin kolmiulotteisen tietojärjestelmän laatutekijämallin mukaisesti ja keskeisiä menestystekijöitä etsittiin. Tutkituissa tapauksissa tietojärjestelmien menestyksen taustalta löytyi alan kirjallisuuden kanssa yhtäpitäviä tekijöitä. Myös Adelakunin laatu-ulottuvuusmalli osoittautui validiksi tutkituissa tapauksissa. Keskeisten menestystekijöiden välisistä vuorovaikutussuhteista rakennettiin malli, jota voidaan hyödyntää kyseisen järjestelmän jatkokehityksessä.

The success factors of the Danish energy service industry

The objective of the research was to understand the success factors of the Danish energy service industry. The research phenomenon was studied greatly but the aim was to examine it from the service logic point of view. The research was threefold and it examined the phenomena from the company, industrial and national levels. The purpose of the multi-level study was to understand all the success factors and to examine how they are combined together. First, the research problem was approached through the literature review. After that, the empirical part of the study was conducted as a case study and the data was collected by theme interviews. The collected data was analyzed through theoretical point of view and compared with earlier studies. This study shows that the most important success factor was the country, because it has affected to the other aspects of the success. Because the actors of the industry are linked together tightly, communication and common understanding of business is essential to the industry success. The new energy technologies do not produce directly added value for the customers. This has sifted energy business towards service business, and the customers have been included in the value creation process.

Computational modeling of stented coronary arteries

The application of computational fluid dynamics (CFD) and finite element analysis (FEA) has been growing rapidly in the various fields of science and technology. One of the areas of interest is in biomedical engineering. The altered hemodynamics inside the blood vessels plays a key role in the development of the arterial disease called atherosclerosis, which is the major cause of human death worldwide. Atherosclerosis is often treated with the stenting procedure to restore the normal blood flow. A stent is a tubular, flexible structure, usually made of metals, which is driven and expanded in the blocked arteries. Despite the success rate of the stenting procedure, it is often associated with the restenosis (re-narrowing of the artery) process. The presence of non-biological device in the artery causes inflammation or re-growth of atherosclerotic lesions in the treated vessels. Several factors including the design of stents, type of stent expansion, expansion pressure, morphology and composition of vessel wall influence the restenosis process. Therefore, the role of computational studies is crucial in the investigation and optimisation of the factors that influence post-stenting complications. This thesis focuses on the stent-vessel wall interactions followed by the blood flow in the post-stenting stage of stenosed human coronary artery. Hemodynamic and mechanical stresses were analysed in three separate stent-plaque-artery models. Plaque was modeled as a multi-layer (fibrous cap (FC), necrotic core (NC), and fibrosis (F)) and the arterial wall as a single layer domain. CFD/FEA simulations were performed using commercial software packages in several models mimicking the various stages and morphologies of atherosclerosis. The tissue prolapse (TP) of stented vessel wall, the distribution of von Mises stress (VMS) inside various layers of vessel wall, and the wall shear stress (WSS) along the luminal surface of the deformed vessel wall were measured and evaluated. The results revealed the role of the stenosis size, thickness of each layer of atherosclerotic wall, thickness of stent strut, pressure applied for stenosis expansion, and the flow condition in the distribution of stresses. The thicknesses of FC, and NC and the total thickness of plaque are critical in controlling the stresses inside the tissue. A small change in morphology of artery wall can significantly affect the distribution of stresses. In particular, FC is the most sensitive layer to TP and stresses, which could determine plaque’s vulnerability to rupture. The WSS is highly influenced by the deflection of artery, which in turn is dependent on the structural composition of arterial wall layers. Together with the stenosis size, their roles could play a decisive role in controlling the low values of WSS (<0.5 Pa) prone to restenosis. Moreover, the time dependent flow altered the percentage of luminal area with WSS values less than 0.5 Pa at different time instants. The non- Newtonian viscosity model of the blood properties significantly affects the prediction of WSS magnitude. The outcomes of this investigation will help to better understand the roles of the individual layers of atherosclerotic vessels and their risk to provoke restenosis at the post-stenting stage. As a consequence, the implementation of such an approach to assess the post-stented stresses will assist the engineers and clinicians in optimizing the stenting techniques to minimize the occurrence of restenosis.