This thesis focuses on experimental characterization, understanding and modelling of nickel-based alloy 718, for a large range of loading conditions. Alloy 718 is the most widely used nickel-based superalloy, due to its high strength, high corrosion resistance and excellent mechanical properties at high temperatures. In this work, the mechanical behavior and microstructure evolution of this alloy during high strain rate deformation is investigated. Compression tests using a Split-Hopkinson pressure bar (SHPB) device were performed and the microstructure of the deformed sample was observed using optical microscope (OM) and scanning-electron microscope (SEM) coupled with electron back-scattered diffraction (EBSD) technique. The microstructural evolution according to the deformation conditions was characterized. For high deformation temperatures (1000 C and above), recrystallisation is identifed as the main deformation mechanism. A physics-based model was employed to simulate the deformation behavior of alloy 718. This type of models accounts for the microstructural mechanisms taking place during deformation. Knowledge about the deformation mechanisms of alloy 718, acquired experimentally and from literature, enables to formulate mathematically the microstructural phenomena governing the deformation behavior of the alloy. The proposed model includes the effects of strain hardening, grain boundary strengthening (Hall-Petch), solid solution strengthening, phonon and electron drag and recovery by dislocation glide and cross-slip. It is calibrated and validated using data obtained from mechanical tests, as well as values captured by the microstructural analysis. / H2020-MSCA-ITN-2017 grant agreement Nº764979 - ENABLE project

This thesis has conducted an extensive character analysis of Sherlock Holmes by comparing the original, authentic detective, as he appears in a corpus consisting of Conan Doyle’s collected works about Holmes, to the characterisation in three select period pastiches. The aim was to analyse to what extent the true characterisation of the famous sleuth has survived in contemporary adaptations, more specifically in the three texts, Sherlock Vs. Dracula (1976), Dr. Jekyll and Mr. Holmes (1979) and Sherlock Holmes and the Angel of the Opera (1994), where the detective encounters equally well-known fictional characters. The novel approach of combining corpus stylistic quantitative methods of characterisation with a qualitative literary approach of identifying similar stylistic and narratological features of characterisation efficiently facilitated an illustration on how Conan Doyle’s round and complex character has endured through adaptations and reimaginings. The corpus investigation on the Sherlock Conan Doyle Corpus supplied an encompassing image of the character, and revealed characteristics absent from the inherent cultural perception. The subsequent cross-comparison between the original in contrast to contemporary characterisations presented clear deviations to the character and further demonstrated a tendency to exaggerate select, generic features that complement the narrative and plot of the integrated novels. Overall, this study concludes that Sherlock Holmes remains the character who travels over time and genres, albeit with a reduced complexity as the respective characterisations in each of the pastiches to various degrees have modified core characteristics significant to the mind-modelling process. That is, through the process of adaptational alterations, the detective has become a flat character. Enough features persist for him to be recognisable and compelling, yet Sherlock Holmes in his entirety subsists merely as a caricature of his original self.

La gazéification de biomasse lignocellulosique en biogaz fait partie des technologies attractives permettant de s’affranchir des énergies fossiles et de valoriser les déchets agricoles ou forestiers. Néanmoins, le développement de cette technologie est freiné par son rendement énergétique faible et la production de polluants (CO2, NOx…). La pyrolyse/gazéification par voie solaire permettrait alors de pallier certains de ces inconvénients (énergie propre et gratuite, process à haute température produisant moins de polluants). Dans ce contexte, l’objectif de cette thèse est de développer une approche expérimentale et numérique afin de maîtriser les procédés de pyrolyse/gazéification de copeaux de bois pour mieux appréhender le développement de la gazéification solaire. D’abord, un travail détaillé de caractérisation des copeaux de bois a été réalisé, alliant diverses analyses des échantillons mais aussi des analyses basées sur l’utilisation d’images tomographiques au rayon X pour déterminer les propriétés morphologiques et, par simulation numérique, les propriétés effectives de transport des copeaux de bois. Ensuite, des essais avec un four-réacteur à échelle laboratoire ont été réalisés pour étudier le séchage, la pyrolyse et la gazéification des copeaux de bois. Ces essais nous ont permis d’étudier l’influence de paramètres comme la température en séchage et en pyrolyse ou le débit de vapeur d’eau en gazéification. En parallèle, un modèle multi-physique pour la simulation de la pyrolyse a été développé. Cet outil a permis une étude détaillé des phénomènes mis en jeu et, in fine, permettrait d’optimiser le système. Enfin, le design d’un gazéifieur solaire a été réalisé. / Thermochemical conversion of lignocellulosic biomass belongs to attractive technologies which are viable routes to reduce reliance on fossil energy and to enhance carbon conversion efficiency. Nevertheless, classical gasification process via autothermal combustion of biomass presents severe drawbacks as bad yield and produced important pollutants. Solar concentrated energy enables high temperature reactions with reduced contaminating gas and higher yield. In this context, this thesis aims at developing experimental and numerical approaches to study detailed mechanism of pyrolysis and gasification processes of wood chips packed bed which are key step toward designing efficient solar gasifier. In a first time, inner properties of wood (initial composition and thermal decomposition) were studied via ultimate and proximate analyzes. Structural and morphological properties of wood chips were computed using image analysis. Effective mass and heat transport properties of the packed bed were assessed via direct numerical simulation combined with X-ray tomographic images. Then a laboratory scale device enabling to characterize pyrolysis and gasification kinetics and gas production was developed. The aim of this experimental work was to understand the impact of parameters such as drying and pyrolysis temperatures, and the steam flow rate during gasification. A multiphysical model of pyrolysis of wood chips packed bed was also developed. It allowed to perform detailed study of pyrolysis physics and in fine it will allow optimizing the pyrolysis/gasification process. Finally, a first design for a solar gasifier was reported and constitutes the basis of further studies.

<p> As space exploration continues to advance, so does the drive to inhabit celestial bodies. In<br> order to expand our civilization to the Moon or even other planets requires an enormous amount of research and development. The Resilient Extra-Terrestrial Habitat Institute is a NASA funded project that aims to develop the technology needed to establish deep-space habitats. Deep-space inhabitation poses many challenges that are not present here on earth. The Moon, for example, has temperatures that range from -233−123°C. Aside from the extreme temperatures, a variety of thermal loads will need to be handled by the Environmental Control and Life Support System (ECLSS). Aside from the research and architecture of the International Space Station’s ECLSS, very little information is known about disturbances related to the thermal management of extra- terrestrial habitats.<br> </p> <p>RETHi is developing a Cyber-Physical Testbed (CPT) that represents a one-fifth scale<br> prototype of a deep space habitat. In order to answer difficult research questions regarding ECLSS and thermal management of a deep-space habitat, a heat pump was modeled and validated with the physical part of the CPT. Once validated, the heat pump model is able to accurately predict the steady state behavior given the indoor and outdoor conditions of the testbed. When coupled with the interior environment (IE) model, it gives insight into the system’s requirements and response. Experimental testing was conducted with the heat pump in order to validate the model. After the model was validated, a series of parametric studies were conducted in order to investigate the effects of varying thermal loads and dehumidification. Since the groundwork was laid through model development and experimentation, future work consists of designing a more versatile heat pump to test a variety of disturbance scenarios. Although the heat pump model is specifically designed for the CPT, it proves to be versatile for other closed and pressurized environments such as aircraft and clean rooms according to the analysis of dehumidification and dependence on pressure. </p>

<p>Electric load forecasting is a critical tool for power system planning and the creation of sustainable energy systems. Precise and reliable load forecasting enables power system operators to make informed decisions regarding power generation and transmission, optimize energy efficiency, and reduce operational costs and extra power generation costs, to further reduce environment-related issues. However, achieving desirable forecasting performance remains challenging due to the irregular, nonstationary, nonlinear, and noisy nature of the observed data under unprecedented events. In recent years, deep learning and other artificial intelligence techniques have emerged as promising approaches for load forecasting. These techniques have the ability to capture complex patterns and relationships in the data and adapt to changing conditions, thereby enhancing forecasting accuracy. As such, the use of deep learning and other artificial intelligence techniques in load forecasting has become an increasingly popular research topic in the field of power systems. </p> <p>Although deep learning techniques have advanced load forecasting, the field still requires more accurate and efficient models. One promising approach is federated learning, which allows for distributed data analysis without exchanging data among multiple devices or cen- ters. This method is particularly relevant for load forecasting, where each power station’s data is sensitive and must be protected. In this study, a proposed approach utilizing Federated Deeponet for seven different power stations is introduced, which proposes a Federated Deep Operator Networks and a Lagevin Dynamics-based Federated Deep Operator Networks using Stochastic Gradient Langevin Dynamics as the optimizer for training the data daily for one-day and predicting for one-day frequencies by frequencies. The data evaluation methods include mean absolute percentage error and the percentage coverage under confidence interval. The findings demonstrate the potential of federated learning for secure and precise load forecasting, while also highlighting the challenges and opportunities of implementing this approach in real-world scenarios. </p>

<p>Breast cancer affects 12.5\% of women over their life time and tissue expansion (TE) is the most common technique for breast reconstruction after mastectomy. However, the rate of complications with TE can be as high as 15\%. Even though the first documented case of TE happened in 1957, there has yet to be a standardized procedure established due to the variations among patients and the TE protocols are currently designed based on surgeon's experience. There are several studies of computational and theoretical framework modeling skin growth in TE but these tools are not used in the clinical setting. This dissertation focuses on bridging the gap between the already existing skin growth modeling efforts and it's potential application in the clinical setting.</p> <p><br></p> <p>We started with calibrating a skin growth model based on porcine skin expansions data. We built a predictive finite element model of tissue expansion. Two types of model were tested, isotropic and anisotropic models. Calibration was done in a probabilistic framework, allowing us to capture the inherent biological uncertainty of living tissue. We hypothesized that the skin growth rate was proportional to stretch. Indeed, the Bayesian calibration process confirmed that this conceptual model best explained the data. </p> <p><br></p> <p>Although the initial model described the macroscale response, it did not consider any activity on the cellular level. To account for the underlying cellular mechanisms at the microscopic scale, we have established a new system of differential equations that describe the dynamics of key mechanosensing pathways that we observed to be activated in the porcine model. We calibrated the parameters of the new model based on porcine skin data. The refined model is still able to reproduce the observed macroscale changes in tissue growth, but now based on mechanistic knowledge of the cell mechanobiology.  </p> <p><br></p> <p>Lastly, we demonstrated how our skin growth model can be used in a clinical setting. We created TE simulations matching the protocol used in human patients and compared the results with clinical data with good agreement. Then we established a personalized model built from 3D scans of a patient unique geometry. We verified our model by comparing the skin growth area with the area of the skin harvested in the procedure, again with good agreement.</p> <p><br></p> <p>Our work shows that skin growth modeling can be a powerful tool to aid surgeons design TE procedures before they are actually performed. The simulations can help with optimizing the protocol to guarantee the correct amount of skin is growth in the shortest time possible without subjecting the skin to deformations that can compromise the procedure.</p>

<p>The document describes the computational framework to optimize spring-driven Autoinjectors. It involves Bayesian Optimization for efficient and cost-effective design of Autoinjectors.</p>

The demand for Advanced High Strength Steel (AHSS) in the automotive industry is increasing day by day. It is mainly motivated by the fact that AHSS can be used as thin sheets while having high strengths. It enables weight reduction of the automobiles which consequently increases the fuel efficiency and has proven to be less harmful to the environment. It is also expected that AHSS will have even higher strength in the near future. Cold work tools steels with 5 wt.% Cr are commonly used to process AHSS. Therefore, the tool steel must meet the challenges in the future, i.e. have even higher hardness, compressive strength and toughness. One way of increasing the mechanical properties of the tool steel is by improving the heat treatment parameters. However, it is not possible without a deeper understanding of the heat treatment process. Therefore, this work presents investigations related to phase transformations occurring in a 5 wt.% Cr cold work tool steel during heat treatment. Furthermore, the influence of austenitisation and tempering temperatures on the microstructure and mechanical properties were investigated. The studies revealed that a higher austenitisation temperature can be used to achieve a higher hardness, good compressive strength and adequate toughnessof the steel. However, too high austenitisation temperature may result inexcessive coarsening of prior austenite grains which reduced the impact toughness. It was also found that retained austenite can transform during tempering by two different mechanisms. Firstly, when tempering at 525°C, carbides precipitate in retained austenite lowering its stability and permitting a transformation to marten site on cooling. Secondly, when tempering at 600°Cfor extended holding time retained austenite isothermally transforms to ferrite and carbides. This occurs by precipitation of carbides in retained austenite followed by a final transformation to ferrite and carbides.These results were used to understand the standard tempering procedure of the 5 wt.% Cr cold work tool steel. Furthermore, alternative heat treatment procedures are discussed based on the important findings presented in this thesis.

<p dir="ltr">The ability to change the shape of aerodynamic surfaces is necessary for modern aircraft, both to provide control while performing maneuvers and to meet the conflicting requirements of various flight conditions such as takeoff/landing and level cruise. These shape changes have traditionally been accomplished through the use of various mechanical devices actuating discrete aerodynamic surfaces, for example ailerons and flaps. Such control surfaces and high-lift devices are generally limited to their specific functionality and create surface discontinuities which increase drag and aircraft noise. Broadly speaking, the design and study of morphing wings typically seeks to improve the performance of aircraft by completing one or more of the following objectives: reducing the drag from discontinuities in the aerodynamic surface of the wing by closing hinge gaps and creating smooth transitions, reducing weight and/or mechanical complexity by integrating mechanism functionality into compliant structures that can bear aerodynamic load and maintain shape adaptability, and providing unique or optimal functionality to the aircraft by allowing it to adjust its aerodynamic shape to meet the needs of various flight conditions with conflicting objectives and constraints.</p><p dir="ltr">The concepts proposed in this work represent potential methods for addressing these objectives. In each case, a compliant structure with multiple stable states is embedded into the wing. Exploiting elastic structural instabilities in this way provides the advantage that a structure can be made relatively stiff while still allowing for large deformations. In the first case, the development of a 3D-printable rib with an embedded bistable element creates a truss-like 2D structure that allows for modification of the airfoil. Switching states of the elements changes their local stiffness, and therefore the global stiffness of the system. By optimizing the topology of the airfoil, a passive deflection of the trailing edge can be leveraged to change the camber to leverage different lift characteristics for varying operating conditions. Primary work on this concept has included the construction of multiple experimental demonstrators for validating the concept through static structural and wind tunnel testing. In the second case, a cellular material has been investigated incorporating a bistable unit cell with a sinusoidal arch. This provides a metamaterial that can exhibit large, reversible deformations with as many stable configurations as there are rows in the honeycomb. This metamaterial is incorporated into a beam-like structure which can serve as a spar for a spanwise morphing wing, providing sufficient bending and torsional stiffness, particularly when utilized at the wing tip. Extending and retracting the wing by switching the states of the honeycomb rows provides a significant change to the wing’s induced drag and wing loading, making it ideal for optimal flight in both loitering and cruising conditions. Contributions to this concept have been the development and characterization of the bistable unit cell and honeycomb, as well as the design and analysis of the metabeam and morphing wing concept.</p>

<p dir="ltr">Precise measurement of the flowrate is crucial for both process control and energy consumption evaluation. The main aim of this work is to develop a methodology to calibrate mechanical flowmeters, designed to measure high viscosity fluids, in water. In order to accomplish this, a series of computational fluid dynamics (CFD) analysis are carried out to determine how the motion of the mechanical component varies with different flow rates of water and high viscosity fluids. This data is recorded and analyzed to develop calibration curves that relate the motion of the mechanical component the flow rates. From the calibration curves, it can be determined the required water flow rate to achieve the equivalent motion of the mechanical component in a specified viscosity. This method provides an efficient and cost-effective calibration process because it eliminates the need for calibrating using heated engine oil to achieve the fluid viscosity of the flow meter is designed. Flowmeter sensitivity analysis was also performed and it was observed that the motion of the mechanical component curves converges as the size of the flowmeter increases suggesting that the effect of viscosity on flowmeter sensitivity decreases as the size of the flowmeter is increased, likely due to reduced resistance to flow and smaller pressure drops. </p><p dir="ltr">The Kanbara Reactor ladle is a commonly used method in the steelmaking industry for hot-metal desulfurization pre-treatment. The impeller's configuration is pivotal to the reactor's performance, yet its precise function remains partially understood. This study introduces a 3-dimensional Volume-of-Fluid (VOF) model integrated with the sliding mesh technique, investigating the influence of five different impeller speeds. After Validating the model through experimental data, this numerical model is applied to investigate the typical developmental phenomena and the consequences of impeller speed variations on fluid flow characteristics, interface profile, and vortex core depth. The findings reveal that the rotational impeller induces a double-recirculation flow pattern in the axial direction due to the centrifugal discharging flow. With increasing impeller rotation speed, the vortex core depth also rises, emphasizing the substantial impact of impeller speed on vortex core depth.</p>