Höyry- ja kaasuturbiinin mallintaminen prosessisimulointiohjelmaan

Tässä diplomityössä on mallinnettu höyry- ja kaasuturbiini Balas -prosessisimulointi-ohjelmaan. Balas on Valtion Teknillisen Tutkimuskeskuksen kehittämä simulointiohjelma, erityisesti paperi- ja selluteollisuuden prosessien staattiseen simulointiin. Työn tavoitteena on kehittää simulointimallit höyry- ja kaasuturbiinille, sekä tutkia niiden toimivuutta vertaamalla simulointeja mittaus- ja mitoitustietoihin. Työssä on muodostettu matemaattiset mallit höyryturbiinille, höyryturbiinin säätövyöhykkeelle sekä höyryturbiinin off-design laskennalle. Kaasuturbiinille muodostettiin toimintakäyrät, joiden avulla tarkastellaan sen toimintaa off-design tilanteessa. Komponentit mallinnettiin diplomityövaiheessa Matlab-ympäristöön, josta ne siirretään Balasiin erillisessä työvaiheessa. Malleissa on kiinnitetty huomiota erityisesti niiden helppokäyttöisyyteen ja monipuolisuuteen. Höyryturbiinimalleja testattiin simuloimalla erään paperitehtaan yhteydessä toimivan voimalaitoksen vastapaineturbiini säätövyöhykkeineen ja vertaamalla simulointituloksia tehtaan mittaustietoihin. Kaasuturbiinimallia testattiin vertaamalla GE Power MS 7001 kaasuturbiinin mitoitustietoja vastaavilla parametreilla simuloituun tapaukseen.

Sustainable Waste-to-Energy Production: Performance Evaluation of Distributed Generation fuelled by Landfill Gas

The environmental impact of landfill is a growing concern in waste management practices. Thus, assessing the effectiveness of the solutions implemented to alter the issue is of importance. The objectives of the study were to provide an insight of landfill advantages, and to consolidate landfill gas importance among others alternative fuels. Finally, a case study examining the performances of energy production from a land disposal at Ylivieska was carried out to ascertain the viability of waste to energy project. Both qualitative and quantitative methods were applied. The study was conducted in two parts; the first was the review of literatures focused on landfill gas developments. Specific considerations were the conception of mechanism governing the variability of gas production and the investigation of mathematical models often used in landfill gas modeling. Furthermore, the analysis of two main distributed generation technologies used to generate energy from landfill was carried out. The review of literature revealed a high influence of waste segregation and high level of moisture content for waste stabilization process. It was found that the enhancement in accuracy for forecasting gas rate generation can be done with both mathematical modeling and field test measurements. The result of the case study mainly indicated the close dependence of the power output with the landfill gas quality and the fuel inlet pressure.

Operatiivisen toiminnan liikevaihdon seurantajärjestelmä

Tämä työ tehdään Steveco Oy:lle sataman operatiivisen toiminnan aiheuttamien kulujen ja tuottojen seurantaan. Työssä käsitellään automaattisen liikevaihdon laskennan ongelmia ja ratkaisuja. Työssä sivutaan myös työajanseurannan sosiaalisia vaikutuksia työntekijöihin, sekä esitetään keinoja ongelmatilanteiden välttämiseksi. Työn tuottavuuden mittaamiseksi on kehitetty matemaattisia malleja, joita voidaan soveltaa organisaatiossa työtehojen mittaamiseksi. Työssä esitellään näitä malleja sekä pohditaan niiden soveltamista. Työssä esitetään malli automaattiseen liikevaihdon ja kulujen laskentaan sekä siihen liittyviä teknisiä ratkaisuja. Työn lopussa todetaan että automaattinen liikevaihdon ja kulujen seurantajärjestelmä on mahdollista rakentaa ja tuloksessa päästään hyvin tarkkaan arvioon lopullisesta liikevaihdosta. Arvion tarkkuus riippuu operatiivisten järjestelmien käyttötavoista sekä työnohjauksen menettelytavoista.

Parallel-Operating Three-Phase Voltage Source Inverters – Circulating CurrentModeling, Analysis and Mitigation

The maximum realizable power throughput of power electronic converters may be limited or constrained by technical or economical considerations. One solution to this problemis to connect several power converter units in parallel. The parallel connection can be used to increase the current carrying capacity of the overall system beyond the ratings of individual power converter units. Thus, it is possible to use several lower-power converter units, produced in large quantities, as building blocks to construct high-power converters in a modular manner. High-power converters realized by using parallel connection are needed for example in multimegawatt wind power generation systems. Parallel connection of power converter units is also required in emerging applications such as photovoltaic and fuel cell power conversion. The parallel operation of power converter units is not, however, problem free. This is because parallel-operating units are subject to overcurrent stresses, which are caused by unequal load current sharing or currents that flow between the units. Commonly, the term ’circulatingcurrent’ is used to describe both the unequal load current sharing and the currents flowing between the units. Circulating currents, again, are caused by component tolerances and asynchronous operation of the parallel units. Parallel-operating units are also subject to stresses caused by unequal thermal stress distribution. Both of these problemscan, nevertheless, be handled with a proper circulating current control. To design an effective circulating current control system, we need information about circulating current dynamics. The dynamics of the circulating currents can be investigated by developing appropriate mathematical models. In this dissertation, circulating current models aredeveloped for two different types of parallel two-level three-phase inverter configurations. Themodels, which are developed for an arbitrary number of parallel units, provide a framework for analyzing circulating current generation mechanisms and developing circulating current control systems. In addition to developing circulating current models, modulation of parallel inverters is considered. It is illustrated that depending on the parallel inverter configuration and the modulation method applied, common-mode circulating currents may be excited as a consequence of the differential-mode circulating current control. To prevent the common-mode circulating currents that are caused by the modulation, a dual modulator method is introduced. The dual modulator basically consists of two independently operating modulators, the outputs of which eventually constitute the switching commands of the inverter. The two independently operating modulators are referred to as primary and secondary modulators. In its intended usage, the same voltage vector is fed to the primary modulators of each parallel unit, and the inputs of the secondary modulators are obtained from the circulating current controllers. To ensure that voltage commands obtained from the circulating current controllers are realizable, it must be guaranteed that the inverter is not driven into saturation by the primary modulator. The inverter saturation can be prevented by limiting the inputs of the primary and secondary modulators. Because of this, also a limitation algorithm is proposed. The operation of both the proposed dual modulator and the limitation algorithm is verified experimentally.

Bayesian methods for estimation, optimization and experimental design

Mathematical models often contain parameters that need to be calibrated from measured data. The emergence of efficient Markov Chain Monte Carlo (MCMC) methods has made the Bayesian approach a standard tool in quantifying the uncertainty in the parameters. With MCMC, the parameter estimation problem can be solved in a fully statistical manner, and the whole distribution of the parameters can be explored, instead of obtaining point estimates and using, e.g., Gaussian approximations. In this thesis, MCMC methods are applied to parameter estimation problems in chemical reaction engineering, population ecology, and climate modeling. Motivated by the climate model experiments, the methods are developed further to make them more suitable for problems where the model is computationally intensive. After the parameters are estimated, one can start to use the model for various tasks. Two such tasks are studied in this thesis: optimal design of experiments, where the task is to design the next measurements so that the parameter uncertainty is minimized, and model-based optimization, where a model-based quantity, such as the product yield in a chemical reaction model, is optimized. In this thesis, novel ways to perform these tasks are developed, based on the output of MCMC parameter estimation. A separate topic is dynamical state estimation, where the task is to estimate the dynamically changing model state, instead of static parameters. For example, in numerical weather prediction, an estimate of the state of the atmosphere must constantly be updated based on the recently obtained measurements. In this thesis, a novel hybrid state estimation method is developed, which combines elements from deterministic and random sampling methods.

Stochastic variability of output levels in a pulp mill

Quite often, in the construction of a pulp mill involves establishing the size of tanks which will accommodate the material from the various processes in which case estimating the right tank size a priori would be vital. Hence, simulation of the whole production process would be worthwhile. Therefore, there is need to develop mathematical models that would mimic the behavior of the output from the various production units of the pulp mill to work as simulators. Markov chain models, Autoregressive moving average (ARMA) model, Mean reversion models with ensemble interaction together with Markov regime switching models are proposed for that purpose.

Dynaamisen lämmönsiirtomallin kehittäminen

Dynaamisia simulointimalleja tarvitaan, jotta voidaan tarkastella järjestelmän käyttäytymistä ajan funktiona. Simulointimallilla voidaan simuloida järjestelmän lähtö erilaisilla herätteillä. Mallin avulla saadaan myös tarkempi käsitys järjestelmästä ja sen osa-alueista, koska simulointimallista voidaan tarkastella sellaisia asioita, jotka voivat olla oikeasta järjestelmästä vaikeasti mitattavia. Tässä työssä kehitetään LUT Energian hyötysuhdemittapaikan keskikokoista kalorimetriä approksimoiva dynaaminen lämmönsiirtomalli käyttäen Matlab® Simulink -ohjelmistoa. Kehitetyn lämmönsiirtomallin tarkkuutta arvioidaan todellisella järjestelmällä tehdyillä mittauksilla. Työssä käytetään karkeita approksimaatioita, jotka tulee korvata tarkemmilla matemaattisilla malleilla jatkokehitystä varten. Työssä kehitetty dynaaminen lämmönsiirtomalli approksimoi todellisen järjestelmän vastetta lämmitysvaiheessa keskimääräisenvirheen ±0,19 °C tarkkuudella.

Regulation of cell fate by c-FLIP phosphorylation

Programmed cell death is an important physiological cellular process that maintains homeostasis and protects multicellular organisms from diseases. Apoptosis is the principal mode of cell death, which eliminates unwanted cells and an enormous effort has been made to understand the molecular mechanisms of the signaling pathway and its regulatory systems. Irregular apoptosis often has life-threatening consequences to humans, including cancer, autoimmune diseases and degenerative diseases. In cancer for example, cell death is an attractive target to eradicate uncontrollably proliferating cells that have disregard pro-apoptotic signaling. Targeted therapeutic approaches are not as effective as once expected, since now we know that the cell death pathways are not sole entities in cells, but are highly associated with various cellular processes. Proteins that regulate apoptosis can also control non-apoptotic signaling pathways. For example, c-FLIP is a protein that can either inhibit or promote caspase-8 activation, which is required to induce apoptosis. Not only has c-FLIP opposing effects on initiating apoptosis, but it also regulates various pro-survival signaling pathways in the cell. It is well known that protein expression level is a determinant of how c-FLIP can regulate different signaling pathways, but other regulatory mechanisms potentially affecting the role of c-FLIP are less well understood. This work addresses novel insights into the mechanisms of c-FLIP post-translational modifications and their functional consequences. We have identified that phosphorylation is an important inception for subcellular localization of c-FLIP, thereby dictating which apoptotic and non-apoptotic signaling pathways c-FLIP could regulate to promote cell survival. Furthermore, we have constructed mathematical models to unite independent studies to establish more systematic c-FLIP signaling pathways to understand the dynamics of extrinsically-induced apoptosis.

Chromatographic recovery of chemicals from acidic biomass hydrolysates

Lignocellulosic biomasses (e.g., wood and straws) are a potential renewable source for the production of a wide variety of chemicals that could be used to replace those currently produced by petrochemical industry. This would lead to lower greenhouse gas emissions and waste amounts, and to economical savings. There are many possible pathways available for the manufacturing of chemicals from lignocellulosic biomasses. One option is to hydrolyze the cellulose and hemicelluloses of these biomasses into monosaccharides using concentrated sulfuric acid as catalyst. This process is an efficient method for producing monosaccharides which are valuable platforn chemicals. Also other valuable products are formed in the hydrolysis. Unfortunately, the concentrated acid hydrolysis has been deemed unfeasible mainly due to high chemical consumption resulting from the need to remove sulfuric acid from the obtained hydrolysates prior to the downstream processing of the monosaccharides. Traditionally, this has been done by neutralization with lime. This, however, results in high chemical consumption. In addition, the by-products formed in the hydrolysis are not removed and may, thus, hinder the monosaccharide processing. In order to improve the feasibility of the concentrated acid hydrolysis, the chemical consumption should be decreased by recycling of sulfuric acid without neutralization. Furthermore, the monosaccharides and the other products formed in the hydrolysis should be recovered selectively for efficient downstream processing. The selective recovery of the hydrolysis by-products would have additional economical benefits on the process due to their high value. In this work, the use of chromatographic fractionation for the recycling of sulfuric acid and the selective recovery of the main components from the hydrolysates formed in the concentrated acid hydrolysis was investigated. Chromatographic fractionation based on the electrolyte exclusion with gel type strong acid cation exchange resins in acid (H+) form as a stationary phase was studied. A systematic experimental and model-based study regarding the separation task at hand was conducted. The phenomena affecting the separation were determined and their effects elucidated. Mathematical models that take accurately into account these phenomena were derived and used in the simulation of the fractionation process. The main components of the concentrated acid hydrolysates (sulfuric acid, monosaccharides, and acetic acid) were included into this model. Performance of the fractionation process was investigated experimentally and by simulations. Use of different process options was also studied. Sulfuric acid was found to have a significant co-operative effect on the sorption of the other components. This brings about interesting and beneficial effects in the column operations. It is especially beneficial for the separation of sulfuric acid and the monosaccharides. Two different approaches for the modelling of the sorption equilibria were investigated in this work: a simple empirical approach and a thermodynamically consistent approach (the Adsorbed Solution theory). Accurate modelling of the phenomena observed in this work was found to be possible using the simple empirical models. The use of the Adsorbed Solution theory is complicated by the nature of the theory and the complexity of the studied system. In addition to the sorption models, a dynamic column model that takes into account the volume changes of the gel type resins as changing resin bed porosity was also derived. Using the chromatography, all the main components of the hydrolysates can be recovered selectively, and the sulfuric acid consumption of the hydrolysis process can be lowered considerably. Investigation of the performance of the chromatographic fractionation showed that the highest separation efficiency in this separation task is obtained with a gel type resin with a high crosslinking degree (8 wt. %); especially when the hydrolysates contain high amounts of acetic acid. In addition, the concentrated acid hydrolysis should be done with as low sulfuric acid concentration as possible to obtain good separation performance. The column loading and flow rate also have large effects on the performance. In this work, it was demonstrated that when recycling of the fractions obtained in the chromatographic fractionation are recycled to preceding unit operations these unit operations should included in the performance evaluation of the fractionation. When this was done, the separation performance and the feasibility of the concentrated acid hydrolysis process were found to improve considerably. Use of multi-column chromatographic fractionation processes, the Japan Organo process and the Multi-Column Recycling Chromatography process, was also investigated. In the studied case, neither of these processes could compete with the single-column batch process in the productivity. However, due to internal recycling steps, the Multi-Column Recycling Chromatography was found to be superior to the batch process when the product yield and the eluent consumption were taken into account.

Simulation of wind powered hydraulic heating system

The objective of this master’s thesis was to design and simulate a wind powered hydraulic heating system that can operate independently in remote places where the use of electricity is not possible. Components for the system were to be selected in such a way that the conditions for manufacture, use and economic viability are the as good as possible. Savonius rotor was chosen for wind turbine, due to its low cut in speed and robust design. Savonius rotor produces kinetic energy in wide wind speed range and it can withstand high wind gusts. Radial piston pump was chosen for the flow source of the hydraulic heater. Pump type was selected due to its characteristics in low rotation speeds and high efficiency. Volume flow from the pump is passed through the throttle orifice. Pressure drop over the orifice causes the hydraulic oil to heat up and, thus, creating thermal energy. Thermal energy in the oil is led to radiator where it conducts heat to the environment. The hydraulic heating system was simulated. For this purpose a mathematical models of chosen components were created. In simulation wind data gathered by Finnish meteorological institute for 167 hours was used as input. The highest produced power was achieved by changing the orifice diameter so that the rotor tip speed ratio follows the power curve. This is not possible to achieve without using electricity. Thus, for the orifice diameter only one, the optimal value was defined. Results from the simulation were compared with investment calculations. Different parameters effecting the investment profitability were altered in sensitivity analyses in order to define the points of investment profitability. Investment was found to be profitable only with high average wind speeds.

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.

Uncertainty of Efficiency Measurements in Electric Drives

The two central goals of this master's thesis are to serve as a guidebook on the determination of uncertainty in efficiency measurements and to investigate sources of uncertainty in efficiency measurements in the field of electric drives by a literature review, mathematical modeling and experimental means. The influence of individual sources of uncertainty on the total instrumental uncertainty is investigated with the help of mathematical models derived for a balance and a direct air cooled calorimeter. The losses of a frequency converter and an induction motor are measured with the input-output method and a balance calorimeter at 50 and 100 % loads. A software linking features of Matlab and Excel is created to process measurement data, calculate uncertainties and to calculate and visualize results. The uncertainties are combined with both the worst case and the realistic perturbation method and distributions of uncertainty by source are shown based on experimental results. A comparison of the calculated uncertainties suggests that the balance calorimeter determines losses more accurately than the input-output method with a relative RPM uncertainty of 1.46 % compared to 3.78 - 12.74 % respectively with 95 % level of confidence at the 93 % induction motor efficiency or higher. As some principles in uncertainty analysis are open to interpretation the views and decisions of the analyst can have noticeable influence on the uncertainty in the measurement result.