994 resultados para Preference modelling
Resumo:
Studies were conducted to estimate parameters and relationships associated with sub-processes in soil seed banks of oilseed rape in Gorgan, Iran. After one month of burial, seed viability decreased to 39%, with a slope of 2.03% per day, and subsequently decreased with a lower slope of 0.01 until 365 days following burial in the soil. Germinability remained at its highest value in autumn and winter and decreased from spring to the last month of summer. Non-dormant seeds of volunteer oilseed rape did not germinate at temperatures lower than 3.8 ºC and a water potential of -1.4 MPa ºd. The hydrothermal values were 36.2 and 42.9 MPa ºd for sub- and supra-optimal temperatures, respectively. Quantification of seed emergence as influenced by burial depth was performed satisfactorily (R² = 0.98 and RMSE = 5.03). The parameters and relationships estimated here can be used for modelling soil seed bank dynamics or establishing a new model for the environment.
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ABSTRACTThe objective of this study was to evaluate the consumption potential, food preference and use of snail Pomacea canaliculata as a biocontrol agent of four submerged aquatic macrophytes (Ceratophyllumdemersum, Egeriadensa, Egerianajas and Hydrilla verticillata). Two experiments were performed. In the first experiment, the introduction of a snail took place and 10 grams of each macrophyte in plastic containers with 1 liter of water. The assessments of consumption by the snail were performed at each 48 hours, during 12 days. The second experiment was performed in 600 liters microcosms containing five snails in each experimental unit. Fifty grams of each macrophyte were offered the snails at the same time, adding the same amounts after seven, 14, 21 and 30 days. On both trials, the most consumed macrophyte by the P.canaliculata was H.verticillata (7.64 ± 1.0 g 48 h and 50 ± 0.18 g) respectively, significantly differing from the others. However, in the absence of H.verticilata, E.najas and E.densa were consumed. The preference of P.canaliculata for H.verticillata is very interesting, because this plant is exotic and problematic in Brazil, and the snail is one more tool for biological management of submerged aquatic macrophyte H.verticillata.
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In the doctoral dissertation, low-voltage direct current (LVDC) distribution system stability, supply security and power quality are evaluated by computational modelling and measurements on an LVDC research platform. Computational models for the LVDC network analysis are developed. Time-domain simulation models are implemented in the time-domain simulation environment PSCAD/EMTDC. The PSCAD/EMTDC models of the LVDC network are applied to the transient behaviour and power quality studies. The LVDC network power loss model is developed in a MATLAB environment and is capable of fast estimation of the network and component power losses. The model integrates analytical equations that describe the power loss mechanism of the network components with power flow calculations. For an LVDC network research platform, a monitoring and control software solution is developed. The solution is used to deliver measurement data for verification of the developed models and analysis of the modelling results. In the work, the power loss mechanism of the LVDC network components and its main dependencies are described. Energy loss distribution of the LVDC network components is presented. Power quality measurements and current spectra are provided and harmonic pollution on the DC network is analysed. The transient behaviour of the network is verified through time-domain simulations. DC capacitor guidelines for an LVDC power distribution network are introduced. The power loss analysis results show that one of the main optimisation targets for an LVDC power distribution network should be reduction of the no-load losses and efficiency improvement of converters at partial loads. Low-frequency spectra of the network voltages and currents are shown, and harmonic propagation is analysed. Power quality in the LVDC network point of common coupling (PCC) is discussed. Power quality standard requirements are shown to be met by the LVDC network. The network behaviour during transients is analysed by time-domain simulations. The network is shown to be transient stable during large-scale disturbances. Measurement results on the LVDC research platform proving this are presented in the work.
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The purpose of this work is to obtain a better understanding of behaviour of possible ultrasound appliance on fluid media mixing. The research is done in the regard to Newtonian and non-Newtonian fluids. The process of ultrasound appliance on liquids is modelled in COMSOL Multiphysics software. The influence of ultrasound using is introduced as waveform equation. Turbulence modelling is fulfilled by the k-ε model in Newtonian fluid. The modeling of ultrasound assisted mixing in non-Newtonian fluids is based on the power law. To verify modelling results two practical methods are used: Particle Image Velocimetry and measurements of mixing time. Particle Image Velocimetry allows capturing of velocity flow field continuously and presents detailed depiction of liquid dynamics. The second way of verification is the comparison of mixing time of homogeneity. Experimentally achievement of mixing time is done by conductivity measurements. In modelling part mixing time is achieved by special module of COMSOL Multiphysics – the transport of diluted species. Both practical and modelling parts show similar radial mechanism of fluid flow under ultrasound appliance – from the horn tip fluid moves to the bottom and along the walls goes back. Velocity profiles are similar in modelling and experimental part in the case of Newtonian fluid. In the case of non-Newtonian fluid velocity profiles do not agree. The development track of ultrasound-assisted mixing modelling is presented in the thesis.
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We determined whether ANP (atrial natriuretic peptide) concentrations, measured by radioimmunoassay, in the ANPergic cerebral regions involved in regulation of sodium intake and excretion and pituitary gland correlated with differences in sodium preference among 40 Wistar male rats (180-220 g). Sodium preference was measured as mean spontaneous ingestion of 1.5% NaCl solution during a test period of 12 days. The relevant tissues included the olfactory bulb (OB), the posterior and anterior lobes of the pituitary gland (PP and AP, respectively), the median eminence (ME), the medial basal hypothalamus (MBH), and the region anteroventral to the third ventricle (AV3V). We also measured ANP content in the right (RA) and left atrium (LA) and plasma. The concentrations of ANP in the OB and the AP were correlated with sodium ingestion during the preceding 24 h, since an increase of ANP in these structures was associated with a reduced ingestion and vice-versa (OB: r = -0.3649, P<0.05; AP: r = -0.3291, P<0.05). Moreover, the AP exhibited a correlation between ANP concentration and mean NaCl intake (r = -0.4165, P<0.05), but this was not the case for the OB (r = 0.2422). This suggests that differences in sodium preference among individual male rats can be related to variations of AP ANP level. Earlier studies indicated that the OB is involved in the control of NaCl ingestion. Our data suggest that the OB ANP level may play a role mainly in day-to-day variations of sodium ingestion in the individual rat
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Twenty-four surgical patients of both sexes without cardiac, hepatic, renal or endocrine dysfunctions were divided into two groups: 10 cardiac surgical patients submitted to myocardial revascularization and cardiopulmonary bypass (CPB), 3 females and 7 males aged 65 ± 11 years, 74 ± 16 kg body weight, 166 ± 9 cm height and 1.80 ± 0.21 m2 body surface area (BSA), and control, 14 surgical patients not submitted to CPB, 11 female and 3 males aged 41 ± 14 years, 66 ± 14 kg body weight, 159 ± 9 cm height and 1.65 ± 0.16 m2 BSA (mean ± SD). Sodium diclofenac (1 mg/kg, im Voltaren 75® twice a day) was administered to patients in the Recovery Unit 48 h after surgery. Venous blood samples were collected during a period of 0-12 h and analgesia was measured by the visual analogue scale (VAS) during the same period. Plasma diclofenac levels were measured by high performance liquid chromatography. A two-compartment open model was applied to obtain the plasma decay curve and to estimate kinetic parameters. Plasma diclofenac protein binding decreased whereas free plasma diclofenac levels were increased five-fold in CPB patients. Data obtained for analgesia reported as the maximum effect (EMAX) were: 25% VAS (CPB) vs 10% VAS (control), P<0.05, median measured by the visual analogue scale where 100% is equivalent to the highest level of pain. To correlate the effect versus plasma diclofenac levels, the EMAX sigmoid model was applied. A prolongation of the mean residence time for maximum effect (MRTEMAX) was observed without any change in lag-time in CPB in spite of the reduced analgesia reported for these patients, during the time-dose interval. In conclusion, the extent of plasma diclofenac protein binding was influenced by CPB with clinically relevant kinetic-dynamic consequences
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Diethylpropion (DEP) is an amphetamine-like agent used as an anorectic drug. Abuse of DEP has been reported and some restrictions of its use have been recently imposed. The conditioning place preference (CPP) paradigm was used to evaluate the reinforcing properties of DEP in adult male Wistar rats. After initial preferences were determined, animals weighing 250-300 g (N = 7 per group) were conditioned with DEP (10, 15 or 20 mg/kg). Only the dose of 15 mg/kg produced a significant place preference (358 ± 39 vs 565 ± 48 s). Pretreatment with the D1 antagonist SCH 23390 (0.05 mg/kg, sc) 10 min before DEP (15 mg/kg, ip) blocked DEP-induced CPP (418 ± 37 vs 389 ± 31 s) while haloperidol (0.5 mg/kg, ip), a D2 antagonist, 15 min before DEP was ineffective in modifying place conditioning produced by DEP (385 ± 36 vs 536 ± 41 s). These results suggest that dopamine D1 receptors mediate the reinforcing effect of DEP
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The zebrafish (Danio rerio) has been used as a model in neuroscience but knowledge about its behavior is limited. The aim of this study was to determine the preference of this fish species for a dark or light environment. Initially we used a place preference test and in a second experiment we applied an exit latency test. A two-chamber aquarium was used for the preference test. The aquarium consisted of a black chamber and a white chamber. In the first experiment the animal was placed in the aquarium and the time spent in the two compartments was recorded for 10 min. More time was spent in the black compartment (Wilcoxon matched-pairs signed-rank test, T = 7, N1 = N2 = 18, P = 0.0001). In the second experiment the animal was placed in the black or white compartment and the time it took to go from the initial compartment to the opposite one was recorded. The test lasted a maximum of 10 min. The results showed that the animal spent more time to go from the black to the white compartment (Mann-Whitney rank sum test, T = 48, N1 = 9, N2 = 8, P<0.0230). These data suggest that this fish species has a natural preference for a dark environment and this characteristic can be very useful for the development of new behavioral paradigms for fish.
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Innovative gas cooled reactors, such as the pebble bed reactor (PBR) and the gas cooled fast reactor (GFR) offer higher efficiency and new application areas for nuclear energy. Numerical methods were applied and developed to analyse the specific features of these reactor types with fully three dimensional calculation models. In the first part of this thesis, discrete element method (DEM) was used for a physically realistic modelling of the packing of fuel pebbles in PBR geometries and methods were developed for utilising the DEM results in subsequent reactor physics and thermal-hydraulics calculations. In the second part, the flow and heat transfer for a single gas cooled fuel rod of a GFR were investigated with computational fluid dynamics (CFD) methods. An in-house DEM implementation was validated and used for packing simulations, in which the effect of several parameters on the resulting average packing density was investigated. The restitution coefficient was found out to have the most significant effect. The results can be utilised in further work to obtain a pebble bed with a specific packing density. The packing structures of selected pebble beds were also analysed in detail and local variations in the packing density were observed, which should be taken into account especially in the reactor core thermal-hydraulic analyses. Two open source DEM codes were used to produce stochastic pebble bed configurations to add realism and improve the accuracy of criticality calculations performed with the Monte Carlo reactor physics code Serpent. Russian ASTRA criticality experiments were calculated. Pebble beds corresponding to the experimental specifications within measurement uncertainties were produced in DEM simulations and successfully exported into the subsequent reactor physics analysis. With the developed approach, two typical issues in Monte Carlo reactor physics calculations of pebble bed geometries were avoided. A novel method was developed and implemented as a MATLAB code to calculate porosities in the cells of a CFD calculation mesh constructed over a pebble bed obtained from DEM simulations. The code was further developed to distribute power and temperature data accurately between discrete based reactor physics and continuum based thermal-hydraulics models to enable coupled reactor core calculations. The developed method was also found useful for analysing sphere packings in general. CFD calculations were performed to investigate the pressure losses and heat transfer in three dimensional air cooled smooth and rib roughened rod geometries, housed inside a hexagonal flow channel representing a sub-channel of a single fuel rod of a GFR. The CFD geometry represented the test section of the L-STAR experimental facility at Karlsruhe Institute of Technology and the calculation results were compared to the corresponding experimental results. Knowledge was gained of the adequacy of various turbulence models and of the modelling requirements and issues related to the specific application. The obtained pressure loss results were in a relatively good agreement with the experimental data. Heat transfer in the smooth rod geometry was somewhat under predicted, which can partly be explained by unaccounted heat losses and uncertainties. In the rib roughened geometry heat transfer was severely under predicted by the used realisable k − epsilon turbulence model. An additional calculation with a v2 − f turbulence model showed significant improvement in the heat transfer results, which is most likely due to the better performance of the model in separated flow problems. Further investigations are suggested before using CFD to make conclusions of the heat transfer performance of rib roughened GFR fuel rod geometries. It is suggested that the viewpoints of numerical modelling are included in the planning of experiments to ease the challenging model construction and simulations and to avoid introducing additional sources of uncertainties. To facilitate the use of advanced calculation approaches, multi-physical aspects in experiments should also be considered and documented in a reasonable detail.
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Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.
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Effective control and limiting of carbon dioxide (CO₂) emissions in energy production are major challenges of science today. Current research activities include the development of new low-cost carbon capture technologies, and among the proposed concepts, chemical combustion (CLC) and chemical looping with oxygen uncoupling (CLOU) have attracted significant attention allowing intrinsic separation of pure CO₂ from a hydrocarbon fuel combustion process with a comparatively small energy penalty. Both CLC and CLOU utilize the well-established fluidized bed technology, but several technical challenges need to be overcome in order to commercialize the processes. Therefore, development of proper modelling and simulation tools is essential for the design, optimization, and scale-up of chemical looping-based combustion systems. The main objective of this work was to analyze the technological feasibility of CLC and CLOU processes at different scales using a computational modelling approach. A onedimensional fluidized bed model frame was constructed and applied for simulations of CLC and CLOU systems consisting of interconnected fluidized bed reactors. The model is based on the conservation of mass and energy, and semi-empirical correlations are used to describe the hydrodynamics, chemical reactions, and transfer of heat in the reactors. Another objective was to evaluate the viability of chemical looping-based energy production, and a flow sheet model representing a CLC-integrated steam power plant was developed. The 1D model frame was succesfully validated based on the operation of a 150 kWth laboratory-sized CLC unit fed by methane. By following certain scale-up criteria, a conceptual design for a CLC reactor system at a pre-commercial scale of 100 MWth was created, after which the validated model was used to predict the performance of the system. As a result, further understanding of the parameters affecting the operation of a large-scale CLC process was acquired, which will be useful for the practical design work in the future. The integration of the reactor system and steam turbine cycle for power production was studied resulting in a suggested plant layout including a CLC boiler system, a simple heat recovery setup, and an integrated steam cycle with a three pressure level steam turbine. Possible operational regions of a CLOU reactor system fed by bituminous coal were determined via mass, energy, and exergy balance analysis. Finally, the 1D fluidized bed model was modified suitable for CLOU, and the performance of a hypothetical 500 MWth CLOU fuel reactor was evaluated by extensive case simulations.
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Meandering rivers have been perceived to evolve rather similarly around the world independently of the location or size of the river. Despite the many consistent processes and characteristics they have also been noted to show complex and unique sets of fluviomorphological processes in which local factors play important role. These complex interactions of flow and morphology affect notably the development of the river. Comprehensive and fundamental field, flume and theoretically based studies of fluviomorphological processes in meandering rivers have been carried out especially during the latter part of the 20th century. However, as these studies have been carried out with traditional field measurements techniques their spatial and temporal resolution is not competitive to the level achievable today. The hypothesis of this study is that, by exploiting e increased spatial and temporal resolution of the data, achieved by combining conventional field measurements with a range of modern technologies, will provide new insights to the spatial patterns of the flow-sediment interaction in meandering streams, which have perceived to show notable variation in space and time. This thesis shows how the modern technologies can be combined to derive very high spatial and temporal resolution data on fluvio-morphological processes over meander bends. The flow structure over the bends is recorded in situ using acoustic Doppler current profiler (ADCP) and the spatial and temporal resolution of the flow data is enhanced using 2D and 3D CFD over various meander bends. The CFD are also exploited to simulate sediment transport. Multi-temporal terrestrial laser scanning (TLS), mobile laser scanning (MLS) and echo sounding data are used to measure the flow-based changes and formations over meander bends and to build the computational models. The spatial patterns of erosion and deposition over meander bends are analysed relative to the measured and modelled flow field and sediment transport. The results are compared with the classic theories of the processes in meander bends. Mainly, the results of this study follow well the existing theories and results of previous studies. However, some new insights regarding to the spatial and temporal patterns of the flow-sediment interaction in a natural sand-bed meander bend are provided. The results of this study show the advantages of the rapid and detailed measurements techniques and the achieved spatial and temporal resolution provided by CFD, unachievable with field measurements. The thesis also discusses the limitations which remain in the measurement and modelling methods and in understanding of fluvial geomorphology of meander bends. Further, the hydro- and morphodynamic models’ sensitivity to user-defined parameters is tested, and the modelling results are assessed against detailed field measurement. The study is implemented in the meandering sub-Arctic Pulmanki River in Finland. The river is unregulated and sand-bed and major morphological changes occur annually on the meander point bars, which are inundated only during the snow-melt-induced spring floods. The outcome of this study applies to sandbed meandering rivers in regions where normally one significant flood event occurs annually, such as Arctic areas with snow-melt induced spring floods, and where the point bars of the meander bends are inundated only during the flood events.
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Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.
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Bioenergi ses som en viktig del av det nu- och framtida sortimentet av inhemsk energi. Svartlut, bark och skogsavfall täcker mer än en femtedel av den inhemska energianvändningen. Produktionsanläggningar kan fungera ofullständigt och en mängd gas-, partikelutsläpp och tjära produceras samtidigt och kan leda till beläggningsbildning och korrosion. Orsaken till dessa problem är ofta obalans i processen: vissa föreningar anrikas i processen och superjämviktstillstånd är bildas. I denna doktorsavhandling presenteras en ny beräkningsmetod, med vilken man kan beskriva superjämviktstillståndet, de viktigaste kemiska reaktionerna, processens värmeproduktion och tillståndsstorheter samtidigt. Beräkningsmetoden grundar sig på en unik frienergimetod med bivillkor som har utvecklats vid VTT. Den här så kallade CFE-metoden har tidigare utnyttjats i pappers-, metall- och kemiindustrin. Applikationer för bioenergi, vilka är demonstrerade i doktorsavhandlingen, är ett nytt användingsområde för metoden. Studien visade att beräkningsmetoden är väl lämpad för högtemperaturenergiprocesser. Superjämviktstillstånden kan uppstå i dessa processer och det kemiska systemet kan definieras med några bivillkor. Typiska tillämpningar är förbränning av biomassa och svartlut, förgasning av biomassa och uppkomsten av kväveoxider. Också olika sätt att definiera superjämviktstillstånd presenterades i doktorsavhandlingen: empiriska konstanter, empiriska hastighetsuttryck eller reaktionsmekanismer kan användas. Resultaten av doktorsavhandlingen kan utnyttjas i framtiden i processplaneringen och i undersökning av nya tekniska lösningar för förgasning, förbränningsteknik och biobränslen. Den presenterade metoden är ett bra alternativ till de traditionella mekanistiska och fenomenmodeller och kombinerar de bästa delarna av både. --------------------------------------------------------------- Bioenergia on tärkeä osa nykyistä ja tulevaa kotimaista energiapalettia. Mustalipeä, kuori ja metsätähteet kattavat yli viidenneksen kotimaisesta energian kulutuksesta. Tuotantolaitokset eivät kuitenkaan aina toimi täydellisesti ja niiden prosesseissa syntyy erilaisia kaasu- ja hiukkaspäästöjä, tervoja sekä prosessilaitteita kuluttavia saostumia ja ruostumista. Usein syy näihin ongelmiin on prosessissa esiintyvä epätasapainotila: tietyt yhdisteet rikastuvat prosessissa ja muodostavat supertasapainotiloja. Väitöstyössä kehitettiin uusi laskentamenetelmä, jolla voidaan kuvata nämä supertasapainotilat, tärkeimmät niihin liittyvät kemialliset reaktiot, prosessin lämmöntuotanto ja tilansuureet yhtä aikaa. Laskentamenetelmä perustuu VTT:llä kehitettyyn ainutlaatuiseen rajoitettuun vapaaenergiamenetelmään. Tätä niin kutsuttua CFE-menetelmää on aiemmin sovelluttu onnistuneesti muun muassa paperi-, metalli- ja kemianteollisuudessa. Väitöstyössä esitetyt bioenergiasovellukset ovat uusi sovellusalue menetelmälle. Työ osoitti laskentatavan soveltuvan hyvin korkealämpöisiin energiatekniikan prosesseihin, joissa kemiallista systeemiä rajoittavia tekijöitä oli rajallinen määrä ja siten super-tasapainotila saattoi muodostua prosessin aikana. Tyypillisiä sovelluskohteita ovat biomassan ja mustalipeän poltto, biomassan kaasutus ja typpioksidipäästöt. Työn aikana arvioitiin myös erilaisia tapoja määritellä super-tasapainojen muodostumista rajoittavat tekijät. Rajoitukset voitiin tehdä teollisiin mittauksiin pohjautuen, kokeellisia malleja hyödyntäen tai mekanistiseen reaktiokinetiikkaan perustuen. Tulevaisuudessa väitöstyön tuloksia voidaan hyödyntää prosessisuunnittelussa ja tutkittaessa uusia teknisiä ratkaisuja kaasutus- ja polttotekniikoissa sekä biopolttoaineiden tutkimuksessa. Kehitetty menetelmä tarjoaa hyvän vaihtoehdon perinteisille mekanistisille ja ilmiömalleille yhdistäen näiden parhaita puolia.