Development of an HTR-10 model in the Serpent reactor physics code

The use of exact coordinates of pebbles and fuel particles of pebble bed reactor modelling becoming possible in Monte Carlo reactor physics calculations is an important development step. This allows exact modelling of pebble bed reactors with realistic pebble beds without the placing of pebbles in regular lattices. In this study the multiplication coefficient of the HTR-10 pebble bed reactor is calculated with the Serpent reactor physics code and, using this multiplication coefficient, the amount of pebbles required for the critical load of the reactor. The multiplication coefficient is calculated using pebble beds produced with the discrete element method and three different material libraries in order to compare the results. The received results are lower than those from measured at the experimental reactor and somewhat lower than those gained with other codes in earlier studies.

Fluvio-morphological processes of meander bends - Combining conventional field measurements, close-range remote sensing and computational modelling

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.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

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.

Numerical simulation of two-chamber plasma sources using finite element method

Numerical simulation of plasma sources is very important. Such models allows to vary different plasma parameters with high degree of accuracy. Moreover, they allow to conduct measurements not disturbing system balance.Recently, the scientific and practical interest increased in so-called two-chamber plasma sources. In one of them (small or discharge chamber) an external power source is embedded. In that chamber plasma forms. In another (large or diffusion chamber) plasma exists due to the transport of particles and energy through the boundary between chambers.In this particular work two-chamber plasma sources with argon and oxygen as active mediums were onstructed. This models give interesting results in electric field profiles and, as a consequence, in density profiles of charged particles.

Modelling the super-equilibria in thermal biomass conversion : applications and limitations of the constrained free energy method

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.

Remote sensing for three-dimensional modelling of hydromorphology

Successful management of rivers requires an understanding of the fluvial processes that govern them. This, in turn cannot be achieved without a means of quantifying their geomorphology and hydrology and the spatio-temporal interactions between them, that is, their hydromorphology. For a long time, it has been laborious and time-consuming to measure river topography, especially in the submerged part of the channel. The measurement of the flow field has been challenging as well, and hence, such measurements have long been sparse in natural environments. Technological advancements in the field of remote sensing in the recent years have opened up new possibilities for capturing synoptic information on river environments. This thesis presents new developments in fluvial remote sensing of both topography and water flow. A set of close-range remote sensing methods is employed to eventually construct a high-resolution unified empirical hydromorphological model, that is, river channel and floodplain topography and three-dimensional areal flow field. Empirical as well as hydraulic theory-based optical remote sensing methods are tested and evaluated using normal colour aerial photographs and sonar calibration and reference measurements on a rocky-bed sub-Arctic river. The empirical optical bathymetry model is developed further by the introduction of a deep-water radiance parameter estimation algorithm that extends the field of application of the model to shallow streams. The effect of this parameter on the model is also assessed in a study of a sandy-bed sub-Arctic river using close-range high-resolution aerial photography, presenting one of the first examples of fluvial bathymetry modelling from unmanned aerial vehicles (UAV). Further close-range remote sensing methods are added to complete the topography integrating the river bed with the floodplain to create a seamless high-resolution topography. Boat- cart- and backpack-based mobile laser scanning (MLS) are used to measure the topography of the dry part of the channel at a high resolution and accuracy. Multitemporal MLS is evaluated along with UAV-based photogrammetry against terrestrial laser scanning reference data and merged with UAV-based bathymetry to create a two-year series of seamless digital terrain models. These allow the evaluation of the methodology for conducting high-resolution change analysis of the entire channel. The remote sensing based model of hydromorphology is completed by a new methodology for mapping the flow field in 3D. An acoustic Doppler current profiler (ADCP) is deployed on a remote-controlled boat with a survey-grade global navigation satellite system (GNSS) receiver, allowing the positioning of the areally sampled 3D flow vectors in 3D space as a point cloud and its interpolation into a 3D matrix allows a quantitative volumetric flow analysis. Multitemporal areal 3D flow field data show the evolution of the flow field during a snow-melt flood event. The combination of the underwater and dry topography with the flow field yields a compete model of river hydromorphology at the reach scale.

Inventive design and product development of a mechanical element

The thesis is dedicated to enhancement and development of a Mechanism in Company X in order to increase its key parameters and approve its workability. Current Mechanism model is described in details. The basis of various analysis, models and theories that are reflecting the working process of the Mechanism are included in the thesis. According to these three directions of enhancements are chosen: from mechanical, tribological and conceptual points of view. As the result the list of improvements is presented. The new models of Mechanism are built. The efficiency and lifetime value are obtained in accordance with corresponding estimations. The comparative analysis confirms the necessity of conducted changes. Recommendations for the Company X specialists are represented in the thesis. Proposals for deeper research are also suggested.

Modelling Cutting States in Rough Turning of 34CrNiMo6 Steel

Rough turning is an important form of manufacturing cylinder-symmetric parts. Thus far, increasing the level of automation in rough turning has included process monitoring methods or adaptive turning control methods that aim to keep the process conditions constant. However, in order to improve process safety, quality and efficiency, an adaptive turning control should be transformed into an intelligent machining system optimizing cutting values to match process conditions or to actively seek to improve process conditions. In this study, primary and secondary chatter and chip formation are studied to understand how to measure the effect of these phenomena to the process conditions and how to avoid undesired cutting conditions. The concept of cutting state is used to address the combination of these phenomena and the current use of the power capacity of the lathe. The measures to the phenomena are not developed based on physical measures, but instead, the severity of the measures is modelled against expert opinion. Based on the concept of cutting state, an expert system style fuzzy control system capable of optimizing the cutting process was created. Important aspects of the system include the capability to adapt to several cutting phenomena appearing at once, even if the said phenomena would potentially require conflicting control action.

Modelling Energy Consumption of a Switch using Fuzzy-Rule Classifier

The energy consumption of IT equipments is becoming an issue of increasing importance. In particular, network equipments such as routers and switches are major contributors to the energy consumption of internet. Therefore it is important to understand how the relationship between input parameters such as bandwidth, number of active ports, traffic-load, hibernation-mode and their impact on energy consumption of a switch. In this paper, the energy consumption of a switch is analyzed in extensive experiments. A fuzzy rule-based model of energy consumption of a switch is proposed based on the result of experiments. The model can be used to predict the energy saving when deploying new switches by controlling the parameters to achieve desired energy consumption and subsequent performance. Furthermore, the model can also be used for further researches on energy saving techniques such as energy-efficient routing protocol, dynamic link shutdown, etc.

Simulation and material calibration of ultra high strength steel (UHSS) S960 welded joint under static tensile test utilizing finite element method (FEM)

The aim of this work was to calibrate the material properties including strength and strain values for different material zones of ultra-high strength steel (UHSS) welded joints under monotonic static loading. The UHSS is heat sensitive and softens by heat due to welding, the affected zone is heat affected zone (HAZ). In this regard, cylindrical specimens were cut out from welded joints of Strenx® 960 MC and Strenx® Tube 960 MH, were examined by tensile test. The hardness values of specimens’ cross section were measured. Using correlations between hardness and strength, initial material properties were obtained. The same size specimen with different zones of material same as real specimen were created and defined in finite element method (FEM) software with commercial brand Abaqus 6.14-1. The loading and boundary conditions were defined considering tensile test values. Using initial material properties made of hardness-strength correlations (true stress-strain values) as Abaqus main input, FEM is utilized to simulate the tensile test process. By comparing FEM Abaqus results with measured results of tensile test, initial material properties will be revised and reused as software input to be fully calibrated in such a way that FEM results and tensile test results deviate minimum. Two type of different S960 were used including 960 MC plates, and structural hollow section 960 MH X-joint. The joint is welded by BöhlerTM X96 filler material. In welded joints, typically the following zones appear: Weld (WEL), Heat affected zone (HAZ) coarse grained (HCG) and fine grained (HFG), annealed zone, and base material (BaM). Results showed that: The HAZ zone is softened due to heat input while welding. For all the specimens, the softened zone’s strength is decreased and makes it a weakest zone where fracture happens while loading. Stress concentration of a notched specimen can represent the properties of notched zone. The load-displacement diagram from FEM modeling matches with the experiments by the calibrated material properties by compromising two correlations of hardness and strength.

Utilizing analytic modelling process in industrial retail context

Nykypäivän monimutkaisessa ja epävakaassa liiketoimintaympäristössä yritykset, jotka kykenevät muuttamaan tuottamansa operatiivisen datan tietovarastoiksi, voivat saavuttaa merkittävää kilpailuetua. Ennustavan analytiikan hyödyntäminen tulevien trendien ennakointiin mahdollistaa yritysten tunnistavan avaintekijöitä, joiden avulla he pystyvät erottumaan kilpailijoistaan. Ennustavan analytiikan hyödyntäminen osana päätöksentekoprosessia mahdollistaa ketterämmän, reaaliaikaisen päätöksenteon. Tämän diplomityön tarkoituksena on koota teoreettinen viitekehys analytiikan mallintamisesta liike-elämän loppukäyttäjän näkökulmasta ja hyödyntää tätä mallinnusprosessia diplomityön tapaustutkimuksen yritykseen. Teoreettista mallia hyödynnettiin asiakkuuksien mallintamisessa sekä tunnistamalla ennakoivia tekijöitä myynnin ennustamiseen. Työ suoritettiin suomalaiseen teollisten suodattimien tukkukauppaan, jolla on liiketoimintaa Suomessa, Venäjällä ja Balteissa. Tämä tutkimus on määrällinen tapaustutkimus, jossa tärkeimpänä tiedonkeruumenetelmänä käytettiin tapausyrityksen transaktiodataa. Data työhön saatiin yrityksen toiminnanohjausjärjestelmästä.