Ces travaux consistent en l’étude expérimentale et numérique des performances énergétiques d’un prototype de micro-cogénération solaire. L’installation, située sur le campus de l’Université de la Rochelle, fonctionne grâce au couplage d’un champ de capteur solaire cylindro-parabolique de 46,5 m² avec un moteur à vapeur à piston non lubrifié fonctionnant selon le cycle thermodynamique de Hirn. Le système de suivi solaire s’effectue selon deux axes et l’eau est directement évaporée au sein de l’absorbeur des capteurs cylindro-paraboliques. La génération d’électricité est assurée par une génératrice et la récupération des chaleurs fatales doit permettre d’assurer les besoins en chauffage et eau chaude sanitaire d’un bâtiment. La première partie de ces travaux présente les essais réalisés. L’objectif est de réaliser des essais complémentaires pour caractériser le concentrateur solaire, d’étudier les conditions de surchauffe de la vapeur, ainsi que le fonctionnement de l’installation complète en hiver. Ce travail a permis le développement de modèles pour le capteur cylindro-paraboliques, les essais en régime surchauffé ont montré la nécessité d’un appoint pour le fonctionnement d’une telle installation tandis que les essais avec moteur présentent des productions compatibles avec les consommations en électricité et chaleur d’un bâtiment résidentiel. La seconde partie concerne la modélisation des éléments constituant le micro-cogénérateur ainsi que l’intégration de cette installation au bâtiment à l’aide d’un logiciel de simulation thermique dynamique (TRNSYS©). Cette étude propose deux options d’intégration selon le positionnement de l’appoint de chaleur. Pour les deux configurations, des bilans hebdomadaires et annuels sont présentés permettant de discuter les avantages/inconvénients de chaque disposition. Il apparaît que le positionnement de l’appoint sur le circuit primaire permet de piloter la production électrique. L’ajout de l’appoint sur la distribution semble plus facilement réalisable mais empêche le contrôle de la production électrique. / This work consists of the experimental and numerical study of the energy performance of a prototype of solar micro-cogeneration. The facility, located on the campus of the University of La Rochelle, operates by coupling a 46.5 m² parabolic trough solar collector field with an oil-free piston steam engine operating according to the Hirn thermodynamic cycle. The solar tracking system is carried out in two axes and the water is evaporated directly into the absorber of the parabolic trough collectors. Electricity generation is provided by a generator and the recovery of fatal heat must make it possible to meet the heating and domestic hot water needs of a building. The first part of this work presents the tests performed. The objective is to carry out additional tests to characterize the solar concentrator, to study the conditions of steam overheating, as well as the operation of the complete installation in winter. This work has allowed the development of models for the parabolic trough sensor, the tests in overheated mode have shown the need for an extra charge for the operation of such an installation while the tests with motor present productions compatible with the electricity and heat consumption of a residential building. The second part concerns the modelling of the elements constituting the micro-cogenerator as well as the integration of this installation into the building using dynamic thermal simulation software (TRNSYS©). This study proposes two integration options depending on the positioning of the auxiliary heater. For both configurations, weekly and annual reviews are presented to discuss the advantages/disadvantages of each provision. It appears that the positioning of the auxiliary on the primary circuit makes it possible to control the electrical production. The addition of back-up boiler on the distribution seems more easily achievable but prevents the control of power generation.

The principal goal of this Ph.D. Thesis is to contribute to the research on formation of compo- sitional and textural zoning in shallow-level plutons. Processes responsible for emplacement of individual plutons/pulses and the origin of compositional zoning in are addressed in a great detail, from the pluton-scale down to the micro-scale. The main emphasis in the more focused part of this text is on a combination of various quanti- tative data sets from two well-selected plutons (the Říčany Pluton in the Central Bohemian Plu- tonic Complex and the Melechov Pluton in the Moldanubian Batholith). These detailed studies are supported by further research on the Štěnovice, Čistá and Ševětín plutons. In this way we cover the evolution of Variscan magmatism in the heart of Bohemian Massif in its entirety, from Late Devonian till Permian. The thesis is based on combining field and structural studies (including the anisotropy of mag- netic susceptibility, AMS), textural analysis, petrological, geochronological and geochemical methods with geophysical investigations. Mathematical approaches have been designed and applied to the interpretation of geochemical data, with potential applications to other igneous systems. I strongly believe that only such comprehensive studies on well-selected case examples have a...

Optimizing and controlling the heating systems in buildings is one way to decrease their load on the power grid, as well as introduce load flexibility to be used in Demand Response (DR) applications. A requirement in occupied buildings is that the thermal comfort of the residents is guaranteed, making the optimization of heating systems a constrained problem with respect to indoor temperature. Thermal models capable of predicting indoor temperatures over short (24 hour) horizons are one way to guarantee this comfort. The accuracy and computational complexity of these models have the most significant impact on controller performance. The data requirements and the expert knowledge required for model implementation are also important factors, since they determine the development costs and, finally, whether a model is feasible to implement. First a literature study explores current modeling approaches that depend only on time-series sensor data and that are suited for control applications. A modeling type found to be fit for such purposes are grey-box models, specifically physically inspired inverse models whose parameters are estimated based on data, such as Resistance- Capacitance (RC) models. This modeling of a dynamical system approach uses prior information in the form of the assumed physical equations and has the potential to increase the performance on sparse data problems. The simple form of the model also has a low level of complexity, making it well suited for control applications. However, expert knowledge can be needed for choosing the model equations as well as initializing the parameters. Then the effects of varying RC model complexity, parameter initialization, and training data are investigated in the case study. The chosen models are 1R1C, 2R2C, and 3R2C. They are fitted using the Nelder-Mead algorithm and validated using the data collected from the RISE Research Villa. Parameter initializations are varied by two orders of magnitude and then fitted on different data sequences to avoid relying on expert knowledge in model creation. The initializations that converged with the best R2 training fit on all sequences were deemed reasonable initializations for the problem and used in the training length comparison. The training length of the models varies from 24 to 384 hours. The results showed that increased training data length correlates positively with performance up to 192 hours for all models, but further increasing it gave inconclusive results. The higher order models evaluated struggled to beat the simplest model or even the constant prediction baseline in Mean Absolute Error (MAE) performance at all training lengths, indicating either that the models selected are unsuitable or that the data features chosen are unrepresentative of the indoor temperature dynamics. Regardless, the MAE errors presented here are comparable to the outcomes of related works. This is possibly an artifact of this dataset having a low variance in temperature and thus resulting in lower errors, which underlines the importance of the data used in case-studies. / Att optimera och styra värmesystemen i byggnader är ett sätt att minska belastningen på elnätet och införa flexibilitet i belastningen som kan användas i tillämpningar för efterfrågeflexibilitet (Demand Response, DR). Ett krav i bebodda byggnader är att de boendes termiska komfort garanteras, vilket gör optimeringen av värmesystemen till ett begränsat problem med avseende på inomhustemperaturen. Termiska modeller som kan förutsäga inomhustemperaturer på kort sikt (24 timmar) är ett sätt att garantera denna komfort. Dessa modellers noggrannhet och beräkningskomplexitet har störst inverkan på styrningens prestanda. Datakraven och den expertkunskap som krävs för att genomföra modellen är också viktiga faktorer, eftersom de avgör utvecklingskostnaderna och slutligen om en modell är möjlig att implementera. Först görs en litteraturstudie av nuvarande modelleringsmetoder som endast är beroende av tidsserier av sensordata och som lämpar sig för reglertillämpningar. En modelleringstyp som visat sig vara lämplig för sådana ändamål är grey-box-modeller, särskilt fysikaliskt inspirerade inversa modeller vars parametrar estimeras på basis av data, t.ex. RC-modeller (Resistance-Capacitance). Denna modell av ett dynamiskt system modellering använder förhandsinformation i form av de antagna fysiska ekvationerna och har potential att öka prestandan vid problem med begränsad data. Modellens enkla form har också en låg komplexitetsnivå, vilket gör den väl lämpad för kontrolltillämpningar. Expertkunskap kan dock behövas för att välja modellekvationer och initiera parametrarna. Därefter undersöks effekterna av att variera RC-modellens komplexitet, parameterinitialisering och träningsdata i fallstudien. De valda modellerna är 1R1C, 2R2C och 3R2C. De tränas med hjälp av Nelder-Mead-algoritmen och valideras med hjälp av data som samlats in från RISE Research Villa. Initialiseringarna av parametrarna varieras med två storleksordningar och anpassas sedan på olika dataserier för att undvika att förlita sig på expertkunskap vid skapandet av modellerna. De initialiseringar som konvergerade med den bästa träningsanpassningen R2 på alla sekvenser ansågs vara rimliga initialiseringar för problemet och användes i jämförelsen av träningslängden. Modellernas träningslängd varierar mellan 24 och 384 timmar. Resultaten visade att en ökad längd på träningsdata korrelerar positivt med prestanda upp till 192 timmar för alla modeller, men att ytterligare ökning inte ger några entydiga resultat. De utvärderade modellerna av högre ordning hade svårt att överträffa den enklaste modellen eller till och med referensmodellen med konstant prediktion i fråga om genomsnittligt absolut fel (MAE) vid alla träningslängder, vilket tyder antingen på att de valda modellerna är olämpliga eller att de valda datafunktionerna inte är representativa för inomhustemperaturens dynamik. Oavsett detta är de MAE-fel som presenteras här jämförbara med resultaten från relaterade studier. Detta är möjligen en artefakt av att detta dataset har en låg varians i temperaturen och därmed resulterar i lägre fel, vilket understryker vikten av de data som används i fallstudier.

A significant challenge with permanent magnet synchronous motors (PMSMs) is thermal management. Thermal stress can lead to irreversible damage to components, and to enable efficient cooling, a thermal model is needed. In this thesis paper, methods for estimating the hot spot temperature of the windings in PMSMs used in heavy-duty EVs are investigated. The methods include black-box models and lumped parameter thermal network-based models. The results reveal that the implemented models are not sufficient for achieving the desired accuracy, and indicate that more parts of the windings need to be considered.

In general, electric propulsion offers very high efficiency but relatively low thrust. To remedy this, several ion engines can be assembled in a clustered configuration and operated in parallel. This requires the careful design of a frame to accommodate the individual propulsion systems. This frame must be modular to be used in different cluster sizes, and verify thermal and mechanical requirements to ensure the nominal operation of the thrusters. The present report aims to show the design process of such a frame, from preliminary modelling to the experimental study of a prototype. This document features an overview of the iterative design process driven by thermal simulations rendered on COMSOL Multiphysics. This process led to the conception of a 2-thruster and 4-thruster cluster frame. A lumped-parameter model of the electric propulsion system was also created to model its complex thermal behaviour. In addition, the 2-thruster frame was studied mechanically with analytical calculations and simulations of simple load cases on SolidWorks. Lastly, a prototype based on the 2-thruster frame model was assembled. The prototype was used to conduct temperature measurements while hosting two operating thrusters inside a vacuum chamber. The temperature distribution in the cluster was measured, and compared to simulation results. Thermal simulations of the 2-thruster and 4-thruster frame showed promising results, while mechanical simulations of the 2-thruster version met all requirements. Moreover, experimental results largely agreed with thermal simulations of the prototype. Finally, the lumped-element model proved instrumental in calibrating the models, with its high flexibility and quick computation time. / Generellt erbjuder elektrisk framdrivning hög verkningsgrad men relativt låg dragkraft. För att avhjälpa detta kan flera jonmotorer sättas samman i en klusterkonfiguration och drivs parallellt. Detta kräver en noggrann utformning av en ram för att rymma de enskilda framdrivningssystemen. Denna ram måste vara modulär för att kunna användas i olika klusterstorlekar och verifiera termiska och mekaniska krav för att säkerställa den nominella driften av motorerna. Föreliggande rapport syftar till att visa designprocessen för en sådan ram, från preliminär modellering till experimentell studie av en prototyp. Detta dokument innehåller en översikt över den iterativa designprocessen, driven av termiska simuleringar gjorda med COMSOL Multiphysics, som ledde till uppfattningen av en 2 motorer och 4 motorer ram. En klumpelementmodell av jonmotorn skapades också för att modellera dess komplexa termiska beteende. Dessutom var den 2 motorer ram studeras mekaniskt med analytiska beräkningar och simuleringar av enkla laddafall med SolidWorks. Slutligen monterades en prototyp baserad på den 2 motorer rammodellen. Prototypen användes för att göra temperaturmätningar medan den är värd för 2 jonmotorer i en vakuumkammare. Temperaturfördelningen i klustret mättes och jämfördes med simuleringsresultat. Termiska simuleringar av den 2 motorer och 4 motorer ramen visade lovande resultat, medan mekaniska simuleringar av den 2 motorer versionen klarade alla krav. Dessutom överensstämde experimentella resultat till stor del med termiska simuleringar av prototypen. Slutligen var klumpelementmodellen mycket användbar för att kalibrera de andra modellerna med sin höga flexibilitet och snabba beräkningstid.

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Human body temperature is an important indicator of physical performance and condition in terms of comfort, heat or cold stress. The aim of this research was to develop Temperature Sensing Fabric (TSF) for continuous temperature measurement in healthcare applications. The study covers the development and manufacture of TSF by embedding fine metallic wire into the structure of textile material using a commercial computerised knitting machine. The operational principle of TSF is based on the inherent propensity of a metal wire to respond to changes in temperature with variation in its electrical resistance. Over 60 TSF samples were developed with combinations of different sensing elements, two inlay densities and highly textured polyester yarn as the base material. TSF samples were created using either bare or insulated wires with a range of diameters from 50 to 150 μm and metal wires of nickel, copper, tungsten, and nickel coated copper. In order to investigate the Temperature-Resistance (T-R) relationship of TSF samples for calibration purposes, a customised test rig was developed and monitoring software was created in the LabVIEW environment, to record the temperature and resistance signals simultaneously. TSF samples were tested in various thermal environments, under laboratory conditions and in practical wear trials, to analyse the relationship between the temperature and resistance of the sensing fabric and to develop base line specifications such as sensitivity, resistance ratio, precision, nominal resistance, and response time; the influence of external parameters such as humidity and strain were also monitored. The regression uncertainty was found to be less than in ±0.1°C; the repeatability uncertainty was found to be less than ±0.5°C; the manufacturing uncertainty in terms of nominal resistance was found to be ± 2% from its mean. The experimental T-R relationship of TSF was validated by modelling in the thermo-electrical domain in both steady and transient states. A maximum error of 0.2°C was found between the experimental and modelled T-R relationships. TSF samples made with bare wire sensing elements showed slight variations in their resistance during strain tests, however, samples made with insulated sensing elements did not demonstrate any detectable strain-dependent-resistance error. The overall thermal response of TSF was found to be affected by basal fabric thickness and mass; the effect of RH was not found to be significant. TSF samples with higher-resistance sensing elements performed better than lower-resistance types. Furthermore, TSF samples made using insulated wire were more straightforward to manufacture because of their increased tensile strength and exhibited better sensing performance than samples made with bare wire. In all the human body wear trials, under steady-state and dynamic conditions both sensors followed the same trends and exhibited similar movement artifacts. When layers of clothing were worn over the sensors, the difference between the response of the TSF and a high-precision reference temperature were reduced by the improved isothermal conditions near the measurement site.

Additive Manufacturing (AM) is an innovative manufacturing process which offers near-net shape fabrication of complex components, directly from CAD models, without dies or substantial machining, resulting in a reduction in lead-time, waste, and cost. For example, the buy-to-fly ratio for a titanium component machined from forged billet is typically 10-20:1 compared to 5-7:1 when manufactured by AM. However, the production rates for most AM processes are relatively slow and AM is consequently largely of interest to the aerospace, automotive and biomedical industries. In addition, the solidification conditions in AM with the Ti alloy commonly lead to undesirable coarse columnar primary β grain structures in components. The present research is focused on developing a fundamental understanding of the influence of the processing conditions on microstructure and texture evolution and their resulting effect on the mechanical properties during additive manufacturing with a Ti6Al4V alloy, using three different techniques, namely; 1) Selective laser melting (SLM) process, 2) Electron beam selective melting (EBSM) process and, 3) Wire arc additive manufacturing (WAAM) process. The most important finding in this work was that all the AM processes produced columnar β-grain structures which grow by epitaxial re-growth up through each melted layer. By thermal modelling using TS4D (Thermal Simulation in 4 Dimensions), it has been shown that the melt pool size increased and the cooling rate decreased from SLM to EBSM and to the WAAM process. The prior β grain size also increased with melt pool size from a finer size in the SLM to a moderate size in EBSM and to huge grains in WAAM that can be seen by eye. However, despite the large difference in power density between the processes, they all had similar G/R (thermal gradient/growth rate) ratios, which were predicted to lie in the columnar growth region in the solidification diagram. The EBSM process showed a pronounced local heterogeneity in the microstructure in local transition areas, when there was a change in geometry; for e.g. change in wall thickness, thin to thick capping section, cross-over’s, V-transitions, etc. By reconstruction of the high temperature β microstructure, it has been shown that all the AM platforms showed primary columnar β grains with a <001>β.