899 resultados para particle trajectory computation
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Position sensitive particle detectors are needed in high energy physics research. This thesis describes the development of fabrication processes and characterization techniques of silicon microstrip detectors used in the work for searching elementary particles in the European center for nuclear research, CERN. The detectors give an electrical signal along the particles trajectory after a collision in the particle accelerator. The trajectories give information about the nature of the particle in the struggle to reveal the structure of the matter and the universe. Detectors made of semiconductors have a better position resolution than conventional wire chamber detectors. Silicon semiconductor is overwhelmingly used as a detector material because of its cheapness and standard usage in integrated circuit industry. After a short spread sheet analysis of the basic building block of radiation detectors, the pn junction, the operation of a silicon radiation detector is discussed in general. The microstrip detector is then introduced and the detailed structure of a double-sided ac-coupled strip detector revealed. The fabrication aspects of strip detectors are discussedstarting from the process development and general principles ending up to the description of the double-sided ac-coupled strip detector process. Recombination and generation lifetime measurements in radiation detectors are discussed shortly. The results of electrical tests, ie. measuring the leakage currents and bias resistors, are displayed. The beam test setups and the results, the signal to noise ratio and the position accuracy, are then described. It was found out in earlier research that a heavy irradiation changes the properties of radiation detectors dramatically. A scanning electron microscope method was developed to measure the electric potential and field inside irradiated detectorsto see how a high radiation fluence changes them. The method and the most important results are discussed shortly.
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Dans cette thèse, nous présentons une nouvelle méthode smoothed particle hydrodynamics (SPH) pour la résolution des équations de Navier-Stokes incompressibles, même en présence des forces singulières. Les termes de sources singulières sont traités d'une manière similaire à celle que l'on retrouve dans la méthode Immersed Boundary (IB) de Peskin (2002) ou de la méthode régularisée de Stokeslets (Cortez, 2001). Dans notre schéma numérique, nous mettons en oeuvre une méthode de projection sans pression de second ordre inspirée de Kim et Moin (1985). Ce schéma évite complètement les difficultés qui peuvent être rencontrées avec la prescription des conditions aux frontières de Neumann sur la pression. Nous présentons deux variantes de cette approche: l'une, Lagrangienne, qui est communément utilisée et l'autre, Eulerienne, car nous considérons simplement que les particules SPH sont des points de quadrature où les propriétés du fluide sont calculées, donc, ces points peuvent être laissés fixes dans le temps. Notre méthode SPH est d'abord testée à la résolution du problème de Poiseuille bidimensionnel entre deux plaques infinies et nous effectuons une analyse détaillée de l'erreur des calculs. Pour ce problème, les résultats sont similaires autant lorsque les particules SPH sont libres de se déplacer que lorsqu'elles sont fixes. Nous traitons, par ailleurs, du problème de la dynamique d'une membrane immergée dans un fluide visqueux et incompressible avec notre méthode SPH. La membrane est représentée par une spline cubique le long de laquelle la tension présente dans la membrane est calculée et transmise au fluide environnant. Les équations de Navier-Stokes, avec une force singulière issue de la membrane sont ensuite résolues pour déterminer la vitesse du fluide dans lequel est immergée la membrane. La vitesse du fluide, ainsi obtenue, est interpolée sur l'interface, afin de déterminer son déplacement. Nous discutons des avantages à maintenir les particules SPH fixes au lieu de les laisser libres de se déplacer. Nous appliquons ensuite notre méthode SPH à la simulation des écoulements confinés des solutions de polymères non dilués avec une interaction hydrodynamique et des forces d'exclusion de volume. Le point de départ de l'algorithme est le système couplé des équations de Langevin pour les polymères et le solvant (CLEPS) (voir par exemple Oono et Freed (1981) et Öttinger et Rabin (1989)) décrivant, dans le cas présent, les dynamiques microscopiques d'une solution de polymère en écoulement avec une représentation bille-ressort des macromolécules. Des tests numériques de certains écoulements dans des canaux bidimensionnels révèlent que l'utilisation de la méthode de projection d'ordre deux couplée à des points de quadrature SPH fixes conduit à un ordre de convergence de la vitesse qui est de deux et à une convergence d'ordre sensiblement égale à deux pour la pression, pourvu que la solution soit suffisamment lisse. Dans le cas des calculs à grandes échelles pour les altères et pour les chaînes de bille-ressort, un choix approprié du nombre de particules SPH en fonction du nombre des billes N permet, en l'absence des forces d'exclusion de volume, de montrer que le coût de notre algorithme est d'ordre O(N). Enfin, nous amorçons des calculs tridimensionnels avec notre modèle SPH. Dans cette optique, nous résolvons le problème de l'écoulement de Poiseuille tridimensionnel entre deux plaques parallèles infinies et le problème de l'écoulement de Poiseuille dans une conduite rectangulaire infiniment longue. De plus, nous simulons en dimension trois des écoulements confinés entre deux plaques infinies des solutions de polymères non diluées avec une interaction hydrodynamique et des forces d'exclusion de volume.
Nonlinear system identification using particle swarm optimisation tuned radial basis function models
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A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.
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We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density function estimation. A particle swarm optimization (PSO) aided orthogonal forward regression (OFR) algorithm based on leave-one-out (LOO) criteria is developed to construct parsimonious radial basis function (RBF) networks with tunable nodes. Each stage of the construction process determines the center vector and diagonal covariance matrix of one RBF node by minimizing the LOO statistics. For regression applications, the LOO criterion is chosen to be the LOO mean square error, while the LOO misclassification rate is adopted in two-class classification applications. By adopting the Parzen window estimate as the desired response, the unsupervised density estimation problem is transformed into a constrained regression problem. This PSO aided OFR algorithm for tunable-node RBF networks is capable of constructing very parsimonious RBF models that generalize well, and our analysis and experimental results demonstrate that the algorithm is computationally even simpler than the efficient regularization assisted orthogonal least square algorithm based on LOO criteria for selecting fixed-node RBF models. Another significant advantage of the proposed learning procedure is that it does not have learning hyperparameters that have to be tuned using costly cross validation. The effectiveness of the proposed PSO aided OFR construction procedure is illustrated using several examples taken from regression and classification, as well as density estimation applications.
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Recent literature has described a “transition zone” between the average top of deep convection in the Tropics and the stratosphere. Here transport across this zone is investigated using an offline trajectory model. Particles were advected by the resolved winds from the European Centre for Medium-Range Weather Forecasts reanalyses. For each boreal winter clusters of particles were released in the upper troposphere over the four main regions of tropical deep convection (Indonesia, central Pacific, South America, and Africa). Most particles remain in the troposphere, descending on average for every cluster. The horizontal components of 5-day trajectories are strongly influenced by the El Niño–Southern Oscillation (ENSO), but the Lagrangian average descent does not have a clear ENSO signature. Tropopause crossing locations are first identified by recording events when trajectories from the same release regions cross the World Meteorological Organization lapse rate tropopause. Most crossing events occur 5–15 days after release, and 30-day trajectories are sufficiently long to estimate crossing number densities. In a further two experiments slight excursions across the lapse rate tropopause are differentiated from the drift deeper into the stratosphere by defining the “tropopause zone” as a layer bounded by the average potential temperature of the lapse rate tropopause and the profile temperature minimum. Transport upward across this zone is studied using forward trajectories released from the lower bound and back trajectories arriving at the upper bound. Histograms of particle potential temperature (θ) show marked differences between the transition zone, where there is a slow spread in θ values about a peak that shifts slowly upward, and the troposphere below 350 K. There forward trajectories experience slow radiative cooling interspersed with bursts of convective heating resulting in a well-mixed distribution. In contrast θ histograms for back trajectories arriving in the stratosphere have two distinct peaks just above 300 and 350 K, indicating the sharp change from rapid convective heating in the well-mixed troposphere to slow ascent in the transition zone. Although trajectories slowly cross the tropopause zone throughout the Tropics, all three experiments show that most trajectories reaching the stratosphere from the lower troposphere within 30 days do so over the west Pacific warm pool. This preferred location moves about 30°–50° farther east in an El Niño year (1982/83) and about 30° farther west in a La Niña year (1988/89). These results could have important implications for upper-troposphere–lower-stratosphere pollution and chemistry studies.
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The Lieb-Oxford bound is a constraint upon approximate exchange-correlation functionals. We explore a nonempirical tightening of that bound in both universal and electron number-dependent form. The test functional is PBE. Regarding both atomization energies (slightly worsened) and bond lengths (slightly improved), we find the PBE functional to be remarkably insensitive to the value of the Lieb-Oxford bound. This both rationalizes the use of the original Lieb-Oxford constant in PBE and suggests that enhancement factors more sensitive to sharpened constraints await discovery.
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The relation between the spin and the mass of an infinite number of particles in a q-deformed dual string theory is studied. For the deformation parameter q a root of unity, in addition to the relation of such values of q with the rational conformal field theory, the Fock space of each oscillator mode in the Fubini-Veneziano operator formulation becomes truncated. Thus, based on general physical grounds, the resulting spin-(mass)2 relation is expected to be below the usual linear trajectory. For such specific values of q, we find that the linear Regge trajectory turns into a square-root trajectory as the mass increases.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Diffusion is a common phenomenon in nature and generally is associated with a system trying to reach a local or a global equilibrium state, as a result of highly irregular individual particle motion. Therefore it is of fundamental importance in physics, chemistry and biology. Particle tracking in complex fluids can reveal important characteristics of its properties. In living cells, we coat the microbead with a peptide (RGD) that binds to integrin receptors at the plasma membrane, which connects to the CSK. This procedure is based on the hypothesis that the microsphere can move only if the structure where it is attached move as well. Then, the observed trajectory of microbeads is a probe of the cytoskeleton (CSK), which is governed by several factors, including thermal diffusion, pressure gradients, and molecular motors. The possibility of separating the trajectories into passive and active diffusion may give information about the viscoelasticity of the cell structure and molecular motors activity. And also we could analyze the motion via generalized Stokes-Einstein relation, avoiding the use of any active techniques. Usually a 12 to 16 Frames Per Second (FPS) system is used to track the microbeads in cell for about 5 minutes. Several factors make this FPS limitation: camera computer communication, light, computer speed for online analysis among others. Here we used a high quality camera and our own software, developed in C++ and Linux, to reach high FPS. Measurements were conducted with samples for 10£ and 20£ objectives. We performed sequentially images with different intervals, all with 2 ¹s exposure. The sequences of intervals are in milliseconds: 4 5 ms (maximum speed) 14, 25, 50 and 100 FPS. Our preliminary results highlight the difference between passive and active diffusion, since the passive diffusion is represented by a Gaussian in the distribution of displacements of the center of mass of individual beads between consecutive frames. However, the active process, or anomalous diffusion, shows as long tails in the distribution of displacements.
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The aim of this work is to present various aspects of numerical simulation of particle and radiation transport for industrial and environmental protection applications, to enable the analysis of complex physical processes in a fast, reliable, and efficient way. In the first part we deal with speed-up of numerical simulation of neutron transport for nuclear reactor core analysis. The convergence properties of the source iteration scheme of the Method of Characteristics applied to be heterogeneous structured geometries has been enhanced by means of Boundary Projection Acceleration, enabling the study of 2D and 3D geometries with transport theory without spatial homogenization. The computational performances have been verified with the C5G7 2D and 3D benchmarks, showing a sensible reduction of iterations and CPU time. The second part is devoted to the study of temperature-dependent elastic scattering of neutrons for heavy isotopes near to the thermal zone. A numerical computation of the Doppler convolution of the elastic scattering kernel based on the gas model is presented, for a general energy dependent cross section and scattering law in the center of mass system. The range of integration has been optimized employing a numerical cutoff, allowing a faster numerical evaluation of the convolution integral. Legendre moments of the transfer kernel are subsequently obtained by direct quadrature and a numerical analysis of the convergence is presented. In the third part we focus our attention to remote sensing applications of radiative transfer employed to investigate the Earth's cryosphere. The photon transport equation is applied to simulate reflectivity of glaciers varying the age of the layer of snow or ice, its thickness, the presence or not other underlying layers, the degree of dust included in the snow, creating a framework able to decipher spectral signals collected by orbiting detectors.
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We consider stochastic individual-based models for social behaviour of groups of animals. In these models the trajectory of each animal is given by a stochastic differential equation with interaction. The social interaction is contained in the drift term of the SDE. We consider a global aggregation force and a short-range repulsion force. The repulsion range and strength gets rescaled with the number of animals N. We show that for N tending to infinity stochastic fluctuations disappear and a smoothed version of the empirical process converges uniformly towards the solution of a nonlinear, nonlocal partial differential equation of advection-reaction-diffusion type. The rescaling of the repulsion in the individual-based model implies that the corresponding term in the limit equation is local while the aggregation term is non-local. Moreover, we discuss the effect of a predator on the system and derive an analogous convergence result. The predator acts as an repulsive force. Different laws of motion for the predator are considered.
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A recent study by the authors points to Charged Particle Drag (CPD) as a contributor to revisit in the LAGEOS non-gravitational perturbations problem. Such perturbations must account for dynamical contributions in the order of pms−2 . The simulated effect takes into account: (i) spatial and temporal variations of the plasmatic parameters (temperature and concentration of the species), (ii) spacecraft potential variations caused by both the eclipse passages and variations in the parameters mentioned above, and (iii) solar and geomagnetic conditions. Furthermore, recent theoretical improvements concerning scattering drag overcome previous limitations allowing for a complete formulation of this effect. For each satellite the lifetime CPD instantaneous acceleration is computed. The plasmatic parameters have been obtained fromthe Sheffield Coupled Thermosphere-Ionosphere-Plasmasphere (SCTIP) semi-empirical model (up to the polar region), as well as alytical/empirical approximations based on spacecraft measurements for the auroral and polar regions. Results show that maximum amplitudes for LAGEOSI are larger than those for LAGEOS-II: −85 pms−2 and −70 pms−2 respectively. This is due to the almost (magnetically) polar orbit configuration of the first, producing larger combinations of plasmatic parameter values. High solar activity has a huge impact in the resulting LAGEOS accelerations: it yields a perfect modulation of the resulting acceleration with maximum amplitudes up to a factor of 10 when comparing low and high activity periods. On the other hand, the impact of the geomagnetic activity results into a reduction of the effect itself, probably due to a decrease in the hydrogen concentration for high energy input periods. The acceleration results will be used in a refined orbit computation in a subsequent investigation.
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Autonomous systems require, in most of the cases, reasoning and decision-making capabilities. Moreover, the decision process has to occur in real time. Real-time computing means that every situation or event has to have an answer before a temporal deadline. In complex applications, these deadlines are usually in the order of milliseconds or even microseconds if the application is very demanding. In order to comply with these timing requirements, computing tasks have to be performed as fast as possible. The problem arises when computations are no longer simple, but very time-consuming operations. A good example can be found in autonomous navigation systems with visual-tracking submodules where Kalman filtering is the most extended solution. However, in recent years, some interesting new approaches have been developed. Particle filtering, given its more general problem-solving features, has reached an important position in the field. The aim of this thesis is to design, implement and validate a hardware platform that constitutes itself an embedded intelligent system. The proposed system would combine particle filtering and evolutionary computation algorithms to generate intelligent behavior. Traditional approaches to particle filtering or evolutionary computation have been developed in software platforms, including parallel capabilities to some extent. In this work, an additional goal is fully exploiting hardware implementation advantages. By using the computational resources available in a FPGA device, better performance results in terms of computation time are expected. These hardware resources will be in charge of extensive repetitive computations. With this hardware-based implementation, real-time features are also expected.
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In tethered satellite technology, it is important to estimate how many electrons a spacecraft can collect from its ambient plasma by a bare electrodynamic tether. The analysis is however very difficult because of the small but significant Geo-magnetic field and the spacecraft’s relative motion to both ions and electrons. The object of our work is the development of a numerical method, for this purpose. Particle-In-Cell (PIC) method, for the calculation of electron current to a positive bare tether moving at orbital velocity in the ionosphere, i.e. in a flowing magnetized plasma under Maxwellian collisionless conditions. In a PIC code, a number of particles are distributed in phase space and the computational domain has a grid on which Poisson equation is solved for field quantities. The code uses the quasi-neutrality condition to solve for the local potential at points in the plasma which coincide with the computational outside boundary. The quasi-neutrality condition imposes ne - ni on the boundary. The Poisson equation is solved in such a way that the presheath region can be captured in the computation. Results show that the collected current is higher than the Orbital Motion Limit (OML) theory. The OML current is the upper limit of current collection under steady collisionless unmagnetized conditions. In this work, we focus on the flowing effects of plasma as a possible cause of the current enhancement. A deficit electron density due to the flowing effects has been worked and removed by introducing adiabatic electron trapping into our model.