Parmi les techniques de détection de rayonnement, les détecteurs optiques occupent une place importante et apportent des réponses aux exigences des expériences de physique et d'astrophysique. Je traiterai plus particulièrement dans mon exposé des techniques de détection basées sur l'émission Čerenkov ou la scintillation dans les matériaux inorganiques transparents, en les illustrant par les recherches, développements et réalisations. Les aspects de science des matériaux, d'optique, en particulier les problèmes causés par les radiations, les techniques expérimentales utilisées, les développements réalisés en matière de simulation numérique et de modélisation, et bien entendu les expériences de physique en cours ou projetées seront abordés. Je terminerai par quelques perspectives d'utilisation des cristaux scintillants dans les calorimètres hadroniques du futur.

Lattice simulations are a popular tool for studying the non-perturbative physics of nonlinear field theories. To perform accurate lattice simulations, a careful account of the discretization error is necessary. Spatial discretization error as a result of lattice spacing dependence in Langevin simulations of anisotropic (2 + 1)-dimensional classical scalar field theories is studied. A transfer integral operator (TIO) method and a one-loop renormalization (1LR) procedure are used to formulate effective potentials. The effective potentials contain counterterms which are intended to suppress the lattice spacing dependence. The two effective potentials were tested numerically in the case of a phi-4 model. A high accuracy modified Euler method was used to evolve a phenomenological Langevin equation. Large scale Langevin simulations were performed in parameter ranges determined to be appropriate. Attempts at extracting correlation lengths as a means of determining effectiveness of each method were not successful. Lattice sizes used in this study were not of a sufficient size to obtain an accurate representation of thermal equilibrium. As an alternative, the initial behaviour of the ensemble field average was observed. Results for the TIO method showed that it was successful at suppressing lattice spacing dependence in a mean field limit. Results for the 1LR method showed that it performed poorly.

This master thesis’s subject is to model an ABB contactor’s dynamics and to develop a hardware-in-the-loop simulation environment. The hardware-in-the-loop method utilizes computer models that are simulated in a real-time simulator. The real-time simulator is connected to hardware components. A contactor is an electrically controlled mechanical switching device and it is used in circuits where large currents can occur. In this thesis, the contactor is divided into three separate subsystems and models are developed for each of them. The three subsystems correspond to the contactor’s mechanics, electromagnetics and electronic components. Computer models are implemented in MATLAB and Simulink to realize the subsystems. The hardware part, of the hardware-in-the-loop simulations, consists of electronic parts that are not modeled. To connect the hardware part to a real-time simulator, from dSPACE, a hardware interface was constructed. This report focuses on the modeling of the mechanics and the electromagnetics as well as the software implementations. The thesis work was carried out in collaboration with another student. The focuses of his report are the modeling of the electronics and the construction of the hardware interface. Validation of the hardware-in-the-loop simulations is done by using measurements collected from a real contactor. The conclusion is that the simulations of the contactor’s behavior correspond well with a real contactor.

Moral contractarianism, as demonstrated in the work of David Gauthier, is an attempt to derive moral principles from the non-moral premises of rational choice. However, this contractarian enterprise runs aground because it is unable to show that agents would commit to norms in a fairly realistic world where knowledge is limited in space and time, where random shocks are likely, and where agents can be arbitrarily differentiated from one another. In a world like this, agents will find that the most "rational" strategy is to behave "non-rationally," imitating the behavior of others in their vicinity and preserving a limited sort of ignorance.

Adsorption processes are widely used for the storage and separation of gases in many industrial and environmental applications. The performance of the process depends strongly on the adsorbent and its interaction with the gases. Therefore, the idea of tailoring the adsorbent to the application by adapting the pore size and/or the chemical composition is very attractive. This work focuses on two groups of customizable hybrid materials: Firstly, in crystalline metal-organic frameworks (MOFs) the chemical and structural properties can be modified by changing the metal-oxide corner or the organic linker. Secondly, periodic mesoporous silica materials can be prepared with different pore sizes and geometries depending on the surfactant and its concentration and additionally modified with organic surface groups. The adsorption behaviour of the materials can be predicted by molecular simulation and thus the influence of modifications can be studied without the need of synthesising the material. For MOFs, the coordinates of the atoms can be obtained from XRD measurements. The quality of the predicted adsorption results was investigated for pure gas (methane, ethane, propane, nitrogen and carbon dioxide) and gas mixture (methane – carbon dioxide) adsorption on the metal-organic framework CuBTC. The comparison showed a good agreement between experimental and simulated results especially at low pressures. In order to create atomistic models for the mesoporous silica structures that are amorphous on the atomistic level, two existing simulation methods to model MCM-41-type materials were combined: micellar structures from coarse grained simulations that capture the phase separation in the surfactant/silica/solvent mixtures were used as input in kinetic Monte Carlo simulation that created the pore model on the atomistic level. The model created with this new methodology showed similar adsorption behaviour compared with a model created only with the kMC method using an ideal geometrical structure as micelle. The influence of modifications of the MOF structures (exchange of metal, linker length/composition and catenation) was investigated by Grand Canonical Monte Carlo simulations for hydrogen adsorption at low temperature and temperature controlled desorption. The peaks in the desorption spectra could be related to steps in the adsorption isotherms at 20 K.

From pharmaceutical powders to agricultural grains, a great proportion of the materials handled in industrial situations are granular or particulate in nature. The variety of stesses that the matierals may experience and the resulting bulk behaviours may be complex. In agricultural engineering, a better understanding into agricultural processes such as seeding, harvesting, transporting and storing will help to improve the handling of agricultural grains with optimised solutions. A detailed understanding of a granular system is crucial when attempting to model a system, whether it is on a micro (particle) or macro (bulk) scale. As numerical capabilities are ever increasing, the Discrete Element Method (DEM) is becoming an increasingly popular numerical technique for computing the behaviour of discrete particels for both industrial and scientific applications. A look into the literature shows a lack of validation of what DEM can predict, specifically with respect to bulk behaviour. In addition, when validation studies are conducted, discrepancies between bulk responses in physical tests and numerical predictions using measured particles properties may arise. The aire of this research is to develop a methodology to calibrate DEM models for agricultural grains using data meaured in bulk physical tests. The methodology will have a wider application to granular solids in general and will advance understanding in the area of DEM model calibration. A contrasting set of granular materials were used to develop the methodology including 3 inorganic solids (single and paired glass beads, and polyethylene terephthalate pellets) and two organic materials (black eyes beans and black kidney beans). The developed methodology consists of three steps: 1. The development of bulk physical tests to measure the bulk responses that will be used to calibrate the DEM models, 2. The creation of the numerical dataset that will describe how the DEM input parameters influence the bulk responses , and 3. The optimisation of the DEM parameters using a searching algorithm and the results from Step 1 and 2. Two laboratory devices were developed to provide calibration data for the proposed methodology: a rotating drum and an confined compression test. These devices were chosen as they can produce bulk responses that are repeatable and easy to quantify, as well as generate discriminating results in numerical simulations when DEM parameters are varied. The bulk response determined from the rotating drum device was the dynamic angle of repose Ør formed when the granular material in a 40% filled drum is rotating at a speed of 7 rpm. the confined compression apparatus was used to determine the bulk stiffness of a system by monitoring the change in void ratio from the stress applied during a loading and unloading cycle. The gradient of the loading and unloadng curves termed λ and κ respectively were chosen as the bulk responses to calibrate the DEM models. The experimental results revealed that the dynamic Ør was significantly influences by the particle aspect ration and boundary conditions. The stiffness parameters were found to be predominantly influences by the initial packing arrangement. The numerical dataset describing how the DEM input parameters influence the numerical bulk responses was created by simulating the bulk physical tests, varying selected DEM parameters and monitoring the effects on bulk parameters. To limit the number of simulations required, design of experiment (DOE) methods were used to determine a reduced factorial matrix of simulations. In additions, an extensive parametric investigation on the non-optimised parameters as well as a scaling sensitivity study was carried out. The final step in determining the optimised parameters is to use a searching algorithm to infer the DEM parameters based on the numerical dataset and used the experimental results as calibration data. To perform a comparative study, tow searching algorithms were explored: the first was a simple method based on Microsoft Excel's Solver algorithm coupled with a weighted inverse distance method. The second made used of the statistical analysis program Statistica. It was shown that the Excel Solver algorithm is simpler and quicker to use but for the present first implementation, could only perform an optimisation based on two bulk responses. Statistica required the creation of a staistical model based on the numerical dataset before using the profiling and desirability searching technique, but was able to optimise the parameter using all three bulk responses. A verification and validation of the optimisation methodology was conducted using the optimised parameters for the black eyed beans. A verification was cnducted by simulating the two calibration experiments using the optimsed parameters and comparing these with the experiments. In addition, a validation was peformed by predicting the response of ta shallow footing penetration on a bed of black eyed beans. It was found that DEM simulations using optimised parameters predicted vertical stress on the footing during penetration to an acceptable degree of accuracy for industrial applications (<10%) at penetration depths up to 30mm.

This thesis presents results from two simulation studies of galaxy formation. In the first project, a dark-matter-only HORIZON simulation is used to investigate the environment and redshift dependence of mass accretion onto haloes and subhaloes. It is found that the halo accretion rate varies less strongly with redshift than predicted by the Extended Press--Schechter formalism, and that low accretion events may drive the radio-mode feedback hypothesized for recent galaxy formation models. The subhaloes at $z<0.5$ in the simulation accrete at higher rates than haloes, on average, and it is argued that this is due to their enhanced clustering at small scales. There is no dependence of accretion rate on environment at $zsim2$, but a weak correlation emerges at $zleq0.5$. The results further support previous suggestions that at $z>1$, dark matter haloes and their associated black holes grew coevally, but imply that haloes could be accreting at fractional rates that are up to a factor of 3--4 higher than their associated black holes by the present day. In the second project, outputs from one of the Adaptive Mesh Refinement NUT simulations are analyzed in order to test whether filamentary flows of cold gas are responsible for the build-up of angular momentum within a Milky Way type disk at $zgeq3$. A set of algorithms are presented that use the resolved physical scale of $12,mathrm{pc}$ to identify: (i) the central gas disk and its plane of orientation; (ii) the complex individual filament trajectories that connect to the disk, and; (iii) the infalling satellites. The results suggest that two filaments at $zgtrsim 5.5$, which later merge to form a single filament at $zlesssim 4$, drive the angular momentum and mass budget of the disk between $3lesssim zlesssim 8$, whereas luminous satellite mergers make negligible fractional contributions. These findings hence provide strong quantitative evidence that the growth of thin disks in low mass haloes at high redshift is supported via inflowing streams of cold gas.

Rare earth ion doped glasses find applications in optical and photonic devices such as optical windows, laser, and optical amplifiers, and as model systems for immobilization of nuclear waste. Macroscopic properties of these materials, such as luminescence efficiency and phase stability, depend strongly on the atomic structure of these glasses. In this thesis, I have studied the atomic level structure of rare earth doped silicate and aluminophosphate glasses by using molecular dynamics simulations. Extensive comparisons with experimental diffraction and NMR data were made to validate the structure models. Insights on the local environments of rare earth ions and their clustering behaviors and their dependence on glass compositions have been obtained. In this thesis, MD simulations have been used to investigate the structure of Eu2O3-doped silica and sodium silicate glasses to understand the glass composition effect on the rare earth ions local environment and their clustering behaviors in the glass matrix, for compositions with low rare earth oxide concentration (~1mol%). It was found that Eu–O distances and coordination numbers were different in silica (2.19-2.22 Å and 4.6-4.8) from those in sodium silicate (2.32 Å and 5.8). High tendencies of Eu clustering and short Eu-Eu distances in the range 3.40-3.90 Å were observed in pure silica glasses as compared to those of silicate glasses with much better dispersed Eu3+ ions and lower probability to form clusters. The results show Eu3+ clustering behavior dependence on the system size and suggest for low doping levels, over 12,000 atoms to obtain statistical meaningful results on the local environment and clustering for rigid silica-based glasses. The structures of four cerium aluminophosphate glasses have also been studied using MD simulations for systems of about 13,000 atoms to investigate aluminum and cerium ion environment and their distribution. P5+ and Al3+ local structures were found stable while those of Ce3+ and Ce4+ ions, through their coordination numbers and bond lengths, are glass composition-dependence. Cerium clusters were found in the high cerium glasses.P5+ coordination numbers around cerium revealed the preference of phosphorus ions in the second coordination shell. Total structure factors from MD simulations and experimental diffraction results show a general agreement from comparison for all the cerium aluminophosphate glasses and with compositional changes up to 25 Å-1. Aluminum enters the phosphate glass network mainly as AlO4 and AlO5 polyhedra only connected through corner sharing to PO4 tetrahedra identified by Q11(1 AlOx), Q12(2 AlOx), Q21(1 AlOx), and Q22(2 AlOx) species.

The study seeks to determine the degree of accumulation of Type II error rates, while violating the assumptions of normality, for different specified levels of power among sample means. The study employs a Monte Carlo simulation procedure with three different specified levels of power, methodologies, and population distributions. On the basis of the comparisons of actual and observed error rates, the following conclusions appear to be appropriate. 1. Under the strict criteria for evaluation of the hypotheses, Type II experimentwise error does accumulate at a rate that the probability of accepting at least one null hypothesis in a family of tests, when in theory all of the alternate hypotheses are true, is high, precluding valid tests at the beginning of the study. 2. The Dunn-Bonferroni procedure of setting the critical value based on the beta value per contrast did not significantly reduce the probability of committing a Type II error in a family of tests. 3. The use of an adequate sample size and orthogonal contrasts, or limiting the number of pairwise comparisons to the number of means, is the best method to control for the accumulation of Type II errors. 4. The accumulation of Type II error is irrespective of distributions.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.