Practical applications of a systematic approach to the chemical abatement of pollutants in water and air

The present dissertation is devoted to the systematic approach to the development of organic toxic and refractory pollutants abatement by chemical decomposition methods in aqueous and gaseous phases. The systematic approach outlines the basic scenario of chemical decomposition process applications with a step-by-step approximation to the most effective result with a predictable outcome for the full-scale application, confirmed by successful experience. The strategy includes the following steps: chemistry studies, reaction kinetic studies in interaction with the mass transfer processes under conditions of different control parameters, contact equipment design and studies, mathematical description of the process for its modelling and simulation, processes integration into treatment technology and its optimisation, and the treatment plant design. The main idea of the systematic approach for oxidation process introduction consists of a search for the most effective combination between the chemical reaction and the treatment device, in which the reaction is supposed to take place. Under this strategy,a knowledge of the reaction pathways, its products, stoichiometry and kinetics is fundamental and, unfortunately, often unavailable from the preliminary knowledge. Therefore, research made in chemistry on novel treatment methods, comprisesnowadays a substantial part of the efforts. Chemical decomposition methods in the aqueous phase include oxidation by ozonation, ozone-associated methods (O3/H2O2, O3/UV, O3/TiO2), Fenton reagent (H2O2/Fe2+/3+) and photocatalytic oxidation (PCO). In the gaseous phase, PCO and catalytic hydrolysis over zero valent ironsare developed. The experimental studies within the described methodology involve aqueous phase oxidation of natural organic matter (NOM) of potable water, phenolic and aromatic amino compounds, ethylene glycol and its derivatives as de-icing agents, and oxygenated motor fuel additives ¿ methyl tert-butyl ether (MTBE) ¿ in leachates and polluted groundwater. Gas-phase chemical decomposition includes PCO of volatile organic compounds and dechlorination of chlorinated methane derivatives. The results of the research summarised here are presented in fifteenattachments (publications and papers submitted for publication and under preparation).

On Modelling, System Identification and Control of Servo-Systems with a Flexible Load

The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.

On diversity effects of alternative agricultural policy reforms in Finland : an agricultural sector modelling approach

Selostus: Maatalouspolitiikkauudistusten vaikutuksista pellonkäytön diversiteettiin

Modelling additional costs caused by a new product feature

Työn tavoitteena oli mallintaa uuden tuoteominaisuuden aiheuttamat lisäkustannukset ja suunnitella päätöksenteon työkalu Timberjack Oy:n kuormatraktorivalmistuksen johtoryhmälle. Tarkoituksena oli luoda karkean tason malli, joka sopisi eri tyyppisten tuoteominaisuuksien kustannuksien selvittämiseen. Uuden tuoteominaisuuden vaikutusta yrityksen eri toimintoihin selvitettiin haastatteluin. Haastattelukierroksen tukena käytettiin kysymyslomaketta. Haastattelujen tavoitteena oli selvittää prosessit, toiminnot ja resurssit, jotka ovat välttämättömiä uuden tuoteominaisuuden tuotantoon saattamisessa ja tuotannossa. Malli suunniteltiin haastattelujen ja tietojärjestelmästä hankitun tiedon pohjalta. Mallin rungon muodostivat ne prosessit ja toiminnot, joihin uudella tuoteominaisuudella on vaikutusta. Huomioon otettiin sellaiset resurssit, joita uusi tuoteominaisuus kuluttaa joko välittömästi, tai välillisesti. Tarkasteluun sisällytettiin ainoastaan lisäkustannukset. Uuden tuoteominaisuuden toteuttamisesta riippumattomat, joka tapauksessa toteutuvat yleiskustannukset jätettiin huomioimatta. Malli on yleistys uuden tuoteominaisuuden aiheuttamista lisäkustannuksista, koska tarkoituksena on, että se sopii eri tyyppisten tuoteominaisuuksien aiheuttamien kustannusten selvittämiseen. Lisäksi malli soveltuu muiden pienehköjen tuotemuutosten kustannusten kartoittamiseen.

Object-Oriented Modelling of Multilayer Networks

Tämä diplomityökuuluu tietoliikenneverkkojen suunnittelun tutkimukseen ja pohjimmiltaan kohdistuu verkon mallintamiseen. Tietoliikenneverkkojen suunnittelu on monimutkainen ja vaativa ongelma, joka sisältää mutkikkaita ja aikaa vieviä tehtäviä. Tämä diplomityö esittelee ”monikerroksisen verkkomallin”, jonka tarkoitus on auttaa verkon suunnittelijoita selviytymään ongelmien monimutkaisuudesta ja vähentää verkkojen suunnitteluun kuluvaa aikaa. Monikerroksinen verkkomalli perustuu yleisille objekteille, jotka ovat yhteisiä kaikille tietoliikenneverkoille. Tämä tekee mallista soveltuvan mielivaltaisille verkoille, välittämättä verkkokohtaisista ominaisuuksista tai verkon toteutuksessa käytetyistä teknologioista. Malli määrittelee tarkan terminologian ja käyttää kolmea käsitettä: verkon jakaminen tasoihin (plane separation), kerrosten muodostaminen (layering) ja osittaminen (partitioning). Nämä käsitteet kuvataan yksityiskohtaisesti tässä työssä. Monikerroksisen verkkomallin sisäinen rakenne ja toiminnallisuus ovat määritelty käyttäen Unified Modelling Language (UML) -notaatiota. Tämä työ esittelee mallin use case- , paketti- ja luokkakaaviot. Diplomityö esittelee myös tulokset, jotka on saatu vertailemalla monikerroksista verkkomallia muihin verkkomalleihin. Tulokset osoittavat, että monikerroksisella verkkomallilla on etuja muihin malleihin verrattuna.

Visual Measurement and Modelling of Tool Wear in Rough Turning

Huolimatta korkeasta automaatioasteesta sorvausteollisuudessa, muutama keskeinen ongelma estää sorvauksen täydellisen automatisoinnin. Yksi näistä ongelmista on työkalun kuluminen. Tämä työ keskittyy toteuttamaan automaattisen järjestelmän kulumisen, erityisesti viistekulumisen, mittaukseen konenäön avulla. Kulumisen mittausjärjestelmä poistaa manuaalisen mittauksen tarpeen ja minimoi ajan, joka käytetään työkalun kulumisen mittaukseen. Mittauksen lisäksi tutkitaan kulumisen mallinnusta sekä ennustamista. Automaattinen mittausjärjestelmä sijoitettiin sorvin sisälle ja järjestelmä integroitiin onnistuneesti ulkopuolisten järjestelmien kanssa. Tehdyt kokeet osoittivat, että mittausjärjestelmä kykenee mittaamaan työkalun kulumisen järjestelmän oikeassa ympäristössä. Mittausjärjestelmä pystyy myös kestämään häiriöitä, jotka ovat konenäköjärjestelmille yleisiä. Työkalun kulumista mallinnusta tutkittiin useilla eri menetelmillä. Näihin kuuluivat muiden muassa neuroverkot ja tukivektoriregressio. Kokeet osoittivat, että tutkitut mallit pystyivät ennustamaan työkalun kulumisasteen käytetyn ajan perusteella. Parhaan tuloksen antoivat neuroverkot Bayesiläisellä regularisoinnilla.

Adaptive MCMC methods with applications in environmental and geophysical models

This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

Modelling of North-West Russian market behavior considering technical restrictions of transmission grid

Nowadays the Finnish-Russian electric energy interaction is carried out through the back-to-back DC Vyborg substation and several power plants working synchronously with Finnish power system. Constant amount of energy flows in one direction — from Russia to Finland. But the process of electricity market development in Russian energy system makes the new possibilities of electrical cooperation available. The goal of master's thesis is to analyze the current state and possible evolution trends of North-West Russian system in relation with future possible change in power flow between Russia and Finland. The research is done by modelling the market of North-West Russia and examination of technical grid restrictions. The operational market models of North-West region of Russia for the years 2008 and 2015 were created during the research process. The description of prepared market models together with modelling results and their analysis are shown in the work. The description of power flow study process and results are also presented.

Reaction Kinetics and Viscosity Modelling in the Fusion Syntheses of Ca- and Ca/Mg-resinates

Rosin is a natural product from pine forests and it is used as a raw material in resinate syntheses. Resinates are polyvalent metal salts of rosin acids and especially Ca- and Ca/Mg- resinates find wide application in the printing ink industry. In this thesis, analytical methods were applied to increase general knowledge of resinate chemistry and the reaction kinetics was studied in order to model the non linear solution viscosity increase during resinate syntheses by the fusion method. Solution viscosity in toluene is an important quality factor for resinates to be used in printing inks. The concept of critical resinate concentration, c crit, was introduced to define an abrupt change in viscosity dependence on resinate concentration in the solution. The concept was then used to explain the non-inear solution viscosity increase during resinate syntheses. A semi empirical model with two estimated parameters was derived for the viscosity increase on the basis of apparent reaction kinetics. The model was used to control the viscosity and to predict the total reaction time of the resinate process. The kinetic data from the complex reaction media was obtained by acid value titration and by FTIR spectroscopic analyses using a conventional calibration method to measure the resinate concentration and the concentration of free rosin acids. A multivariate calibration method was successfully applied to make partial least square (PLS) models for monitoring acid value and solution viscosity in both mid-infrared (MIR) and near infrared (NIR) regions during the syntheses. The calibration models can be used for on line resinate process monitoring. In kinetic studies, two main reaction steps were observed during the syntheses. First a fast irreversible resination reaction occurs at 235 °C and then a slow thermal decarboxylation of rosin acids starts to take place at 265 °C. Rosin oil is formed during the decarboxylation reaction step causing significant mass loss as the rosin oil evaporates from the system while the viscosity increases to the target level. The mass balance of the syntheses was determined based on the resinate concentration increase during the decarboxylation reaction step. A mechanistic study of the decarboxylation reaction was based on the observation that resinate molecules are partly solvated by rosin acids during the syntheses. Different decarboxylation mechanisms were proposed for the free and solvating rosin acids. The deduced kinetic model supported the analytical data of the syntheses in a wide resinate concentration region, over a wide range of viscosity values and at different reaction temperatures. In addition, the application of the kinetic model to the modified resinate syntheses gave a good fit. A novel synthesis method with the addition of decarboxylated rosin (i.e. rosin oil) to the reaction mixture was introduced. The conversion of rosin acid to resinate was increased to the level necessary to obtain the target viscosity for the product at 235 °C. Due to a lower reaction temperature than in traditional fusion synthesis at 265 °C, thermal decarboxylation is avoided. As a consequence, the mass yield of the resinate syntheses can be increased from ca. 70% to almost 100% by recycling the added rosin oil.

Ultrafine grinding of FGD and phosphogypsum with an attrition bead mill and a jet mill : optimisation and modelling of grinding and mill comparison

Fine powders of minerals are used commonly in the paper and paint industry, and for ceramics. Research for utilizing of different waste materials in these applications is environmentally important. In this work, the ultrafine grinding of two waste gypsum materials, namely FGD (Flue Gas Desulphurisation) gypsum and phosphogypsum from a phosphoric acid plant, with the attrition bead mill and with the jet mill has been studied. The ' objective of this research was to test the suitability of the attrition bead mill and of the jet mill to produce gypsum powders with a particle size of a few microns. The grinding conditions were optimised by studying the influences of different operational grinding parameters on the grinding rate and on the energy consumption of the process in order to achieve a product fineness such as that required in the paper industry with as low energy consumption as possible. Based on experimental results, the most influential parameters in the attrition grinding were found to be the bead size, the stirrer type, and the stirring speed. The best conditions, based on the product fineness and specific energy consumption of grinding, for the attrition grinding process is to grind the material with small grinding beads and a high rotational speed of the stirrer. Also, by using some suitable grinding additive, a finer product is achieved with a lower energy consumption. In jet mill grinding the most influential parameters were the feed rate, the volumetric flow rate of the grinding air, and the height of the internal classification tube. The optimised condition for the jet is to grind with a small feed rate and with a large rate of volumetric flow rate of grinding air when the inside tube is low. The finer product with a larger rate of production was achieved with the attrition bead mill than with the jet mill, thus the attrition grinding is better for the ultrafine grinding of gypsum than the jet grinding. Finally the suitability of the population balance model for simulation of grinding processes has been studied with different S , B , and C functions. A new S function for the modelling of an attrition mill and a new C function for the modelling of a jet mill were developed. The suitability of the selected models with the developed grinding functions was tested by curve fitting the particle size distributions of the grinding products and then comparing the fitted size distributions to the measured particle sizes. According to the simulation results, the models are suitable for the estimation and simulation of the studied grinding processes.

Salient Pole Synchronous Machine Modelling in an Industrial Direct Torque Controlled Drive Application

Synchronous motors are used mainly in large drives, for example in ship propulsion systems and in steel factories' rolling mills because of their high efficiency, high overload capacity and good performance in the field weakening range. This, however, requires an extremely good torque control system. A fast torque response and a torque accuracy are basic requirements for such a drive. For large power, high dynamic performance drives the commonly known principle of field oriented vector control has been used solely hitherto, but nowadays it is not the only way to implement such a drive. A new control method Direct Torque Control (DTC) has also emerged. The performance of such a high quality torque control as DTC in dynamically demanding industrial applications is mainly based on the accurate estimate of the various flux linkages' space vectors. Nowadays industrial motor control systems are real time applications with restricted calculation capacity. At the same time the control system requires a simple, fast calculable and reasonably accurate motor model. In this work a method to handle these problems in a Direct Torque Controlled (DTC) salient pole synchronous motor drive is proposed. A motor model which combines the induction law based "voltage model" and motor inductance parameters based "current model" is presented. The voltage model operates as a main model and is calculated at a very fast sampling rate (for example 40 kHz). The stator flux linkage calculated via integration from the stator voltages is corrected using the stator flux linkage computed from the current model. The current model acts as a supervisor that prevents only the motor stator flux linkage from drifting erroneous during longer time intervals. At very low speeds the role of the current model is emphasised but, nevertheless, the voltage model always stays the main model. At higher speeds the function of the current model correction is to act as a stabiliser of the control system. The current model contains a set of inductance parameters which must be known. The validation of the current model in steady state is not self evident. It depends on the accuracy of the saturated value of the inductances. Parameter measurement of the motor model where the supply inverter is used as a measurement signal generator is presented. This so called identification run can be performed prior to delivery or during drive commissioning. A derivation method for the inductance models used for the representation of the saturation effects is proposed. The performance of the electrically excited synchronous motor supplied with the DTC inverter is proven with experimental results. It is shown that it is possible to obtain a good static accuracy of the DTC's torque controller for an electrically excited synchronous motor. The dynamic response is fast and a new operation point is achieved without oscillation. The operation is stable throughout the speed range. The modelling of the magnetising inductance saturation is essential and cross saturation has to be considered as well. The effect of cross saturation is very significant. A DTC inverter can be used as a measuring equipment and the parameters needed for the motor model can be defined by the inverter itself. The main advantage is that the parameters defined are measured in similar magnetic operation conditions and no disagreement between the parameters will exist. The inductance models generated are adequate to meet the requirements of dynamically demanding drives.

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.

Modelling of the PWR PACTEL vertical steam generator with the TRACE code

The behavior of the nuclear power plants must be known in all operational situations. Thermal hydraulics computer applications are used to simulate the behavior of the plants. The computer applications must be validated before they can be used reliably. The simulation results are compared against the experimental results. In this thesis a model of the PWR PACTEL steam generator was prepared with the TRAC/RELAP Advanced Computational Engine computer application. The simulation results can be compared against the results of the Advanced Process Simulator analysis software in future. Development of the model of the PWR PACTEL vertical steam generator is introduced in this thesis. Loss of feedwater transient simulation examples were carried out with the model.