987 resultados para cosmology, numerical simulations, dark matter, dark energy, initial conditions


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Implementation of stable aeroelastic models with the ability to capture the complex features of Multi concept smartblades is a prime step in reducing the uncertainties that come along with blade dynamics. The numerical simulations of fluid structure interaction can thus be used to test a realistic scenarios comprising of full-scale blades at a reasonably low computational cost. A code which was a combination of two advanced numerical models was designed and was run with the help of paralell HPC supercomputer platform. The first model was based on a variation of dimensional reduction technique proposed by Hodges and Yu. This model was the one to record the structural response of heterogenous composite blades. This technique reduces the geometrical complexities of the heterogenous blade section into a stiffness matrix for an equivalent beam. This derived equivalent 1-D strain energy matrix is similar to the actual 3-D strain energy matrix in an asymptotic sense. As this 1-D matrix helps in accurately modeling the blade structure as a 1-D finite element problem, this substantially redues the computational effort and subsequently the computational cost that are required to model the structural dynamics at each step. Second model comprises of implementation of the Blade Element Momentum Theory. In this approach we map all the velocities and the forces with the help of orthogonal matrices that help in capturing the large deformations and the effects of rotations in calculating the aerodynamic forces. This ultimately helps us to take into account the complex flexo torsional deformations. In this thesis we have succesfully tested these computayinal tools developed by MTU’s research team lead by for the aero elastic analysis of wind-turbine blades. The validation in this thesis is majorly based on several experiments done on NREL-5MW blade, as this is widely accepted as a benchmark blade in the wind industry. Along with the use of this innovative model the internal blade structure was also changed to add up to the existing benefits of the already advanced numerical models.

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Nanoparticles are often considered as efficient drug delivery vehicles for precisely dispensing the therapeutic payloads specifically to the diseased sites in the patient’s body, thereby minimizing the toxic side effects of the payloads on the healthy tissue. However, the fundamental physics that underlies the nanoparticles’ intrinsic interaction with the surrounding cells is inadequately elucidated. The ability of the nanoparticles to precisely control the release of its payloads externally (on-demand) without depending on the physiological conditions of the target sites has the potential to enable patient- and disease-specific nanomedicine, also known as Personalized NanoMedicine (PNM). In this dissertation, magneto-electric nanoparticles (MENs) were utilized for the first time to enable important functions, such as (i) field-controlled high-efficacy dissipation-free targeted drug delivery system and on-demand release at the sub-cellular level, (ii) non-invasive energy-efficient stimulation of deep brain tissue at body temperature, and (iii) a high-sensitivity contrasting agent to map the neuronal activity in the brain non-invasively. First, this dissertation specifically focuses on using MENs as energy-efficient and dissipation-free field-controlled nano-vehicle for targeted delivery and on-demand release of a anti-cancer Paclitaxel (Taxol) drug and a anti-HIV AZT 5’-triphosphate (AZTTP) drug from 30-nm MENs (CoFe2O4-BaTiO3) by applying low-energy DC and low-frequency (below 1000 Hz) AC fields to separate the functions of delivery and release, respectively. Second, this dissertation focuses on the use of MENs to non-invasively stimulate the deep brain neuronal activity via application of a low energy and low frequency external magnetic field to activate intrinsic electric dipoles at the cellular level through numerical simulations. Third, this dissertation describes the use of MENs to track the neuronal activities in the brain (non-invasively) using a magnetic resonance and a magnetic nanoparticle imaging by monitoring the changes in the magnetization of the MENs surrounding the neuronal tissue under different states. The potential therapeutic and diagnostic impact of this innovative and novel study is highly significant not only in HIV-AIDS, Cancer, Parkinson’s and Alzheimer’s disease but also in many CNS and other diseases, where the ability to remotely control targeted drug delivery/release, and diagnostics is the key.

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In the study of the spatial characteristics of the visual channels, the power spectrum model of visual masking is one of the most widely used. When the task is to detect a signal masked by visual noise, this classical model assumes that the signal and the noise are previously processed by a bank of linear channels and that the power of the signal at threshold is proportional to the power of the noise passing through the visual channel that mediates detection. The model also assumes that this visual channel will have the highest ratio of signal power to noise power at its output. According to this, there are masking conditions where the highest signal-to-noise ratio (SNR) occurs in a channel centered in a spatial frequency different from the spatial frequency of the signal (off-frequency looking). Under these conditions the channel mediating detection could vary with the type of noise used in the masking experiment and this could affect the estimation of the shape and the bandwidth of the visual channels. It is generally believed that notched noise, white noise and double bandpass noise prevent off-frequency looking, and high-pass, low-pass and bandpass noises can promote it independently of the channel's shape. In this study, by means of a procedure that finds the channel that maximizes the SNR at its output, we performed numerical simulations using the power spectrum model to study the characteristics of masking caused by six types of one-dimensional noise (white, high-pass, low-pass, bandpass, notched, and double bandpass) for two types of channel's shape (symmetric and asymmetric). Our simulations confirm that (1) high-pass, low-pass, and bandpass noises do not prevent the off-frequency looking, (2) white noise satisfactorily prevents the off-frequency looking independently of the shape and bandwidth of the visual channel, and interestingly we proved for the first time that (3) notched and double bandpass noises prevent off-frequency looking only when the noise cutoffs around the spatial frequency of the signal match the shape of the visual channel (symmetric or asymmetric) involved in the detection. In order to test the explanatory power of the model with empirical data, we performed six visual masking experiments. We show that this model, with only two free parameters, fits the empirical masking data with high precision. Finally, we provide equations of the power spectrum model for six masking noises used in the simulations and in the experiments.

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Le développement au cours des dernières décennies de lasers à fibre à verrouillage de modes permet aujourd’hui d’avoir accès à des sources fiables d’impulsions femtosecondes qui sont utilisées autant dans les laboratoires de recherche que pour des applications commerciales. Grâce à leur large bande passante ainsi qu’à leur excellente dissipation de chaleur, les fibres dopées avec des ions de terres rares ont permis l’amplification et la génération d’impulsions brèves de haute énergie avec une forte cadence. Cependant, les effets non linéaires causés par la faible taille du faisceau dans la fibre ainsi que la saturation de l’inversion de population du milieu compliquent l’utilisation d’amplificateurs fibrés pour l’obtention d’impulsions brèves dont l’énergie dépasse le millijoule. Diverses stratégies comme l’étirement des impulsions à des durées de l’ordre de la nanoseconde, l’utilisation de fibres à cristaux photoniques ayant un coeur plus large et l’amplification en parallèle ont permis de contourner ces limitations pour obtenir des impulsions de quelques millijoules ayant une durée inférieure à la picoseconde. Ce mémoire de maîtrise présente une nouvelle approche pour l’amplification d’impulsions brèves utilisant la diffusion Raman des verres de silice comme milieu de gain. Il est connu que cet effet non linéaire permet l’amplification avec une large bande passante et ce dernier est d’ailleurs couramment utilisé aujourd’hui dans les réseaux de télécommunications par fibre optique. Puisque l’adaptation des schémas d’amplification Raman existants aux impulsions brèves de haute énergie n’est pas directe, on propose plutôt un schéma consistant à transférer l’énergie d’une impulsion pompe quasi monochromatique à une impulsion signal brève étirée avec une dérive en fréquence. Afin d’évaluer le potentiel du gain Raman pour l’amplification d’impulsions brèves, ce mémoire présente un modèle analytique permettant de prédire les caractéristiques de l’impulsion amplifiée selon celles de la pompe et le milieu dans lequel elles se propagent. On trouve alors que la bande passante élevée du gain Raman des verres de silice ainsi que sa saturation inhomogène permettent l’amplification d’impulsions signal à une énergie comparable à celle de la pompe tout en conservant une largeur spectrale élevée supportant la compression à des durées très brèves. Quelques variantes du schéma d’amplification sont proposées, et leur potentiel est évalué par l’utilisation du modèle analytique ou de simulations numériques. On prédit analytiquement et numériquement l’amplification Raman d’impulsions à des énergies de quelques millijoules, dont la durée est inférieure à 150 fs et dont la puissance crête avoisine 20 GW.

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Abstract : Recently, there is a great interest to study the flow characteristics of suspensions in different environmental and industrial applications, such as snow avalanches, debris flows, hydrotransport systems, and material casting processes. Regarding rheological aspects, the majority of these suspensions, such as fresh concrete, behave mostly as non-Newtonian fluids. Concrete is the most widely used construction material in the world. Due to the limitations that exist in terms of workability and formwork filling abilities of normal concrete, a new class of concrete that is able to flow under its own weight, especially through narrow gaps in the congested areas of the formwork was developed. Accordingly, self-consolidating concrete (SCC) is a novel construction material that is gaining market acceptance in various applications. Higher fluidity characteristics of SCC enable it to be used in a number of special applications, such as densely reinforced sections. However, higher flowability of SCC makes it more sensitive to segregation of coarse particles during flow (i.e., dynamic segregation) and thereafter at rest (i.e., static segregation). Dynamic segregation can increase when SCC flows over a long distance or in the presence of obstacles. Therefore, there is always a need to establish a trade-off between the flowability, passing ability, and stability properties of SCC suspensions. This should be taken into consideration to design the casting process and the mixture proportioning of SCC. This is called “workability design” of SCC. An efficient and non-expensive workability design approach consists of the prediction and optimization of the workability of the concrete mixtures for the selected construction processes, such as transportation, pumping, casting, compaction, and finishing. Indeed, the mixture proportioning of SCC should ensure the construction quality demands, such as demanded levels of flowability, passing ability, filling ability, and stability (dynamic and static). This is necessary to develop some theoretical tools to assess under what conditions the construction quality demands are satisfied. Accordingly, this thesis is dedicated to carry out analytical and numerical simulations to predict flow performance of SCC under different casting processes, such as pumping and tremie applications, or casting using buckets. The L-Box and T-Box set-ups can evaluate flow performance properties of SCC (e.g., flowability, passing ability, filling ability, shear-induced and gravitational dynamic segregation) in casting process of wall and beam elements. The specific objective of the study consists of relating numerical results of flow simulation of SCC in L-Box and T-Box test set-ups, reported in this thesis, to the flow performance properties of SCC during casting. Accordingly, the SCC is modeled as a heterogeneous material. Furthermore, an analytical model is proposed to predict flow performance of SCC in L-Box set-up using the Dam Break Theory. On the other hand, results of the numerical simulation of SCC casting in a reinforced beam are verified by experimental free surface profiles. The results of numerical simulations of SCC casting (modeled as a single homogeneous fluid), are used to determine the critical zones corresponding to the higher risks of segregation and blocking. The effects of rheological parameters, density, particle contents, distribution of reinforcing bars, and particle-bar interactions on flow performance of SCC are evaluated using CFD simulations of SCC flow in L-Box and T-box test set-ups (modeled as a heterogeneous material). Two new approaches are proposed to classify the SCC mixtures based on filling ability and performability properties, as a contribution of flowability, passing ability, and dynamic stability of SCC.

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Nowadays the development of new Internal Combustion Engines is mainly driven by the need to reduce tailpipe emissions of pollutants, Green-House Gases and avoid the fossil fuels wasting. The design of dimension and shape of the combustion chamber together with the implementation of different injection strategies e.g., injection timing, spray targeting, higher injection pressure, play a key role in the accomplishment of the aforementioned targets. As far as the match between the fuel injection and evaporation and the combustion chamber shape is concerned, the assessment of the interaction between the liquid fuel spray and the engine walls in gasoline direct injection engines is crucial. The use of numerical simulations is an acknowledged technique to support the study of new technological solutions such as the design of new gasoline blends and of tailored injection strategies to pursue the target mixture formation. The current simulation framework lacks a well-defined best practice for the liquid fuel spray interaction simulation, which is a complex multi-physics problem. This thesis deals with the development of robust methodologies to approach the numerical simulation of the liquid fuel spray interaction with walls and lubricants. The accomplishment of this task was divided into three tasks: i) setup and validation of spray-wall impingement three-dimensional CFD spray simulations; ii) development of a one-dimensional model describing the liquid fuel – lubricant oil interaction; iii) development of a machine learning based algorithm aimed to define which mixture of known pure components mimics the physical behaviour of the real gasoline for the simulation of the liquid fuel spray interaction.

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The goal of this simulation thesis is to present a tool for studying and eliminating various numerical problems observed while analyzing the behavior of the MIND cable during fast voltage polarity reversal. The tool is built on the MATLAB environment, where several simulations were run to achieve oscillation-free results. This thesis will add to earlier research on HVDC cables subjected to polarity reversals. Initially, the code does numerical simulations to analyze the electric field and charge density behavior of a MIND cable for certain scenarios such as before, during, and after polarity reversal. However, the primary goal is to reduce numerical oscillations from the charge density profile. The generated code is notable for its usage of the Arithmetic Mean Approach and the Non-Uniform Field Approach for filtering and minimizing oscillations even under time and temperature variations.

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In this doctoral dissertation, a comprehensive methodological approach for the assessment of river embankments safety conditions, based on the integrated use of laboratory testing, physical modelling and finite element (FE) numerical simulations, is proposed, with the aim of contributing to a better understanding of the effect of time-dependent hydraulic boundary conditions on the hydro-mechanical response of river embankments. The case study and materials selected for the present research project are representative for the riverbank systems of Alpine and Apennine tributaries of the main river Po (Northern Italy), which have recently experienced various sudden overall collapses. The outcomes of a centrifuge test carried out under the enhanced gravity field of 50-g, on a riverbank model, made of a compacted silty sand mixture, overlying a homogeneous clayey silt foundation layer and subjected to a simulated flood event, have been considered for the definition of a robust and realistic experimental benchmark. In order to reproduce the observed experimental behaviour, a first set of numerical simulations has been carried out by assuming, for both the embankments and the foundation unit, rigid soil porous media, under partially saturated conditions. Mechanical and hydraulic soil properties adopted in the numerical analyses have been carefully estimated based on standard saturated triaxial, oedometer and constant head permeability tests. Afterwards, advanced suction-controlled laboratory tests, have been carried out to investigate the effect of suction and confining stresses on the shear strength and compressibility characteristics of the filling material and a second set of numerical simulations has been run, taking into account the soil parameters updated based on the most recent tests. The final aim of the study is the quantitative estimation of the predictive capabilities of the calibrated numerical tools, by systematically comparing the results of the FE simulations to the experimental benchmark.

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This coupled model combines two state-of-the-art numerical models, NEMO for the oceanic component and WRF for the atmospheric component and implements them at an appropriate resolution. The oceanic model has been implemented starting from the Mediterranean Forecasting System with a resolution of 1/24° and the domain was extended to exactly match the grid of a newly implemented atmospheric model for the same area. The uncoupled ocean model has been validated against SST observed data, both in the simulation of an extreme event and in the short-term forecast of two seasonal periods. A new setup of the model was successfully tested in which the downward radiative fluxes were prescribed from atmospheric forecasts. Various physical schemes, domain, boundary, and initial conditions were tested with the atmospheric model to obtain the best representation of medicane Ianos. The heat fluxes calculated by the uncoupled models were compared to determine which setup gave the best energy balance between the components of the coupled model. The coupling strategy used is the traditional one, where the ocean is driven by the surface stress, heat fluxes, and radiative fluxes computed in the atmospheric component, which in turn receives the SST and surface currents. As expected, the overall skills of the coupled model are slightly degraded compared to the uncoupled models, even though the positioning and timing of the cyclone at the time of the landfall is enhanced. The mean heat fluxes do not change compared to the uncoupled model, whereas the pattern of the shortwave radiation and latent heat is changed. Moreover, the two energy fluxes are larger in absolute values than those calculated with the MFS formulas. The fact that they have opposite signs give raise to a compensation error that limits the overall degradation of the coupled simulation.

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In this thesis, we perform a next-to-leading order calculation of the impact of primordial magnetic fields (PMF) into the evolution of scalar cosmological perturbations and the cosmic microwave background (CMB) anisotropy. Magnetic fields are everywhere in the Universe at all scales probed so far, but their origin is still under debate. The current standard picture is that they originate from the amplification of initial seed fields, which could have been generated as PMFs in the early Universe. The most robust way to test their presence and constrain their features is to study how they impact on key cosmological observables, in particular the CMB anisotropies. The standard way to model a PMF is to consider its contribution (quadratic in the magnetic field) at the same footing of first order perturbations, under the assumptions of ideal magneto-hydrodynamics and compensated initial conditions. In the perspectives of ever increasing precision of CMB anisotropies measurements and of possible uncounted non-linear effects, in this thesis we study effects which go beyond the standard assumptions. We study the impact of PMFs on cosmological perturbations and CMB anisotropies with adiabatic initial conditions, the effect of Alfvén waves on the speed of sound of perturbations and possible non-linear behavior of baryon overdensity for PMFs with a blue spectral index, by modifying and improving the publicly available Einstein-Boltzmann code SONG, which has been written in order to take into account all second-order contributions in cosmological perturbation theory. One of the objectives of this thesis is to set the basis to verify by an independent fully numerical analysis the possibility to affect recombination and the Hubble constant.

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This thesis is focused on the viscoelastic behavior of macro-synthetic fiber-reinforced concrete (MSFRC) with polypropylene studied numerically when subjected to temperature variations (-30 oC to +60 oC). LDPM (lattice discrete particle model), a meso-scale model for heterogeneous composites, is used. To reproduce the MSFRC structural behavior, an extended version of LDPM that includes fiber effects through fiber-concrete interface micromechanics, called LDPM-F, is applied. Model calibration is performed based on three-point bending, cube, and cylinder test for plain concrete and MSFRC. This is followed by a comprehensive literature study on the variation of mechanical properties with temperature for individual fibers and plain concrete. This literature study and past experimental test results constitute inputs for final numerical simulations. The numerical response of MSFRC three-point bending test is replicated and compared with the previously conducted experimental test results; finally, the conclusions were drawn. LDPM numerical model is successfully calibrated using experimental responses on plain concrete. Fiber-concrete interface micro-mechanical parameters are subsequently fixed and LDPM-F models are calibrated based on MSFRC three-point bending test at room temperature. Number of fibers contributing crack bridging mechanism is computed and found to be in good agreement with experimental counts. Temperature variations model for individual constituents of MSFRC, fibers and plain concrete, are implemented in LDPM-F. The model is validated for MSFRC three-point bending stress-CMOD (crack mouth opening) response reproduced at -30 oC, -15 oC, 0 oC, +20 oC, +40 oC and +60 oC. It is found that the model can well describe the temperature variation behavior of MSFRC. At positive temperatures, simulated responses are in good agreement. Slight disagreement in negative regimes suggests an in-depth study on fiber-matrix interface bond behavior with varying temperatures.

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This work approaches the forced air cooling of strawberry by numerical simulation. The mathematical model that was used describes the process of heat transfer, based on the Fourier's law, in spherical coordinates and simplified to describe the one-dimensional process. For the resolution of the equation expressed for the mathematical model, an algorithm was developed based on the explicit scheme of the numerical method of the finite differences and implemented in the scientific computation program MATLAB 6.1. The validation of the mathematical model was made by the comparison between theoretical and experimental data, where strawberries had been cooled with forced air. The results showed to be possible the determination of the convective heat transfer coefficient by fitting the numerical and experimental data. The methodology of the numerical simulations was showed like a promising tool in the support of the decision to use or to develop equipment in the area of cooling process with forced air of spherical fruits.

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We study how the crossover exponent, phi, between the directed percolation (DP) and compact directed percolation (CDP) behaves as a function of the diffusion rate in a model that generalizes the contact process. Our conclusions are based in results pointed by perturbative series expansions and numerical simulations, and are consistent with a value phi = 2 for finite diffusion rates and phi = 1 in the limit of infinite diffusion rate.

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Thirty-eight stations were sampled in Guanabara Bay, Rio de Janeiro, Brazil, to assess the spatio-temporal diversity and biomass of sublittoral polychaetes. Samples were collected during the dry (September 2000) and rainy season (May 2001) in shallow sublittoral sediments. The polychaete spatial composition showed a heterogeneous distribution throughout the bay. A negative gradient of diversity and biomass was observed towards the inner parts of the bay and sheltered areas. A wide azoic area was found inside the bay. Some high-biomass and low-diversity spots were found near a sewage-discharge point. In these areas, the polychaete biomass increased after the rainy season. A diversified polychaete community was identified around the bay mouth, with no dramatic changes of this pattern between the two sampling periods. Deposit-feeders were dominant in the entire study area. The relative importance of carnivores and omnivores increased towards the outer sector, at stations with coarse sediment fractions. Guanabara Bay can be divided into three main zones with respect to environmental conditions and polychaete diversity and biomass patterns: A) High polychaete diversity, hydrodynamically exposed areas composed of sandy, oxidized or moderately reduced sediments with normoxic conditions in the water column. B) Low diversity and high biomass of deposit and suspension-feeding polychaete species in the middle part of the bay near continental inflows, comprising stations sharing similar proportions of silt, clay and fine sands. C) Azoic area or an impoverished polychaete community in hydrodynamically low-energy areas of silt and clay with extremely reduced sediments, high total organic matter content and hypoxic conditions in the water column, located essentially from the mid-bay towards the north sector. High total organic matter content and hypoxic conditions combined with slow water renewal in the inner bay seemed to play a key role in the polychaete diversity and biomass. Sedimentation processes and organic load coming from untreated sewage into the bay may have negatively affected the survivorship of the fauna.

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The possible states in the flow around two identical circular cylinders in tandem arrangements are investigated for configurations in the vicinity of the drag inversion separation. By means of numerical simulations, the hysteresis in the transition between the shedding regimes is studied and the relationship between (three-dimensional) secondary instabilities and shedding regime determination is addressed. The differences observed in the behavior of two- and three-dimensional flows are analyzed, and the regions of bistable flow are delimited. Very good agreement is found between the proposed scenario and results available in the literature. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3420111]