978 resultados para Physics engine


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Für die vorliegende Arbeit wurde die chemische Zusammensetzung von natürlichen und anthropogenen Aerosolpartikeln untersucht. Zu diesem Zweck wurde das Aerosolmassenspektrometer (AMS) der Firma Aerodyne, Inc. eingesetzt, womit neben den chemischen Substanzen auch die Massengrößenverteilungen der einzelnen Komponenten der Aerosolpartikel in einem Größenbereich zwischen 20 und 1500 nm quantitativ gemessen werden können. Im Rahmen der HAZE2002-Messkampagne am Meteorologischen Observatorium Hohenpeißenberg wurden die Aerosolpartikel aus natürlichen Quellen untersucht. Diese Partikel bestanden aus Sulfat, Nitrat, Ammonium und organischen Komponenten (Organics). Sulfat, Nitrat und Ammonium wiesen den gleichen Durchmesser auf, was auf eine interne Mischung dieser drei chemischen Substanzen in den Partikeln hinwies. Die Organics hatten einen kleineren Durchmesser, was auf jüngere Partikel hindeutete. Die Analyse der organischen Substanzen in den Aerosolpartikeln zeigte, dass diese zu einem großen Teil aus oxidierten Kohlenwasserstoffen bestanden, die während den Nachmittagsstunden gebildet wurden. Die thermische Abhängigkeit der Bildung von Ammoniumnitrat konnte sowohl gemessen als auch mit Hilfe Konzentrationsberechnungen nach [Seinfeld und Pandis, 1998] nachvollzogen werden. Die gemessene Partikelneubildung konnte auf die ternäre Nukleation aus H2SO4/H2O/NH3 zurückgeführt werden. Aerosolpartikel aus anthropogenen Quellen, wie z.B. der motorischen Verbrennung, wurden während der Messungen in Zusammenarbeit mit dem Ford Forschungszentrum in Aachen (FFA) untersucht. Nukleationspartikel (D 45 nm) konnten bei Experimenten auf dem Rollenprüfstand nur bei einer ausreichend hohen Verdünnung, einem hohen Schwefelgehalt im Kraftstoff und einem hohen Lastzustand nachgewiesen werden. Die Messungen an der Autobahn A4 ergaben eine bimodale Massengrößenverteilung der organischen Partikel, wobei die erste Mode Partikeln aus der motorischen Verbrennungen zugeschrieben werden konnte. Aufgrund der guten Charakterisierung stellt das AMS ein vielseitig einsetzbares Aerosolmessgerät dar, welches in einer hohen Zeitauflösung eine quantitative, größenaufgelöste chemische Analyse der zu messenden Aerosolpartikel bereitstellt.

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A polar stratospheric cloud submodel has been developed and incorporated in a general circulation model including atmospheric chemistry (ECHAM5/MESSy). The formation and sedimentation of polar stratospheric cloud (PSC) particles can thus be simulated as well as heterogeneous chemical reactions that take place on the PSC particles. For solid PSC particle sedimentation, the need for a tailor-made algorithm has been elucidated. A sedimentation scheme based on first order approximations of vertical mixing ratio profiles has been developed. It produces relatively little numerical diffusion and can deal well with divergent or convergent sedimentation velocity fields. For the determination of solid PSC particle sizes, an efficient algorithm has been adapted. It assumes a monodisperse radii distribution and thermodynamic equilibrium between the gas phase and the solid particle phase. This scheme, though relatively simple, is shown to produce particle number densities and radii within the observed range. The combined effects of the representations of sedimentation and solid PSC particles on vertical H2O and HNO3 redistribution are investigated in a series of tests. The formation of solid PSC particles, especially of those consisting of nitric acid trihydrate, has been discussed extensively in recent years. Three particle formation schemes in accordance with the most widely used approaches have been identified and implemented. For the evaluation of PSC occurrence a new data set with unprecedented spatial and temporal coverage was available. A quantitative method for the comparison of simulation results and observations is developed and applied. It reveals that the relative PSC sighting frequency can be reproduced well with the PSC submodel whereas the detailed modelling of PSC events is beyond the scope of coarse global scale models. In addition to the development and evaluation of new PSC submodel components, parts of existing simulation programs have been improved, e.g. a method for the assimilation of meteorological analysis data in the general circulation model, the liquid PSC particle composition scheme, and the calculation of heterogeneous reaction rate coefficients. The interplay of these model components is demonstrated in a simulation of stratospheric chemistry with the coupled general circulation model. Tests against recent satellite data show that the model successfully reproduces the Antarctic ozone hole.

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In this work we develop and analyze an adaptive numerical scheme for simulating a class of macroscopic semiconductor models. At first the numerical modelling of semiconductors is reviewed in order to classify the Energy-Transport models for semiconductors that are later simulated in 2D. In this class of models the flow of charged particles, that are negatively charged electrons and so-called holes, which are quasi-particles of positive charge, as well as their energy distributions are described by a coupled system of nonlinear partial differential equations. A considerable difficulty in simulating these convection-dominated equations is posed by the nonlinear coupling as well as due to the fact that the local phenomena such as "hot electron effects" are only partially assessable through the given data. The primary variables that are used in the simulations are the particle density and the particle energy density. The user of these simulations is mostly interested in the current flow through parts of the domain boundary - the contacts. The numerical method considered here utilizes mixed finite-elements as trial functions for the discrete solution. The continuous discretization of the normal fluxes is the most important property of this discretization from the users perspective. It will be proven that under certain assumptions on the triangulation the particle density remains positive in the iterative solution algorithm. Connected to this result an a priori error estimate for the discrete solution of linear convection-diffusion equations is derived. The local charge transport phenomena will be resolved by an adaptive algorithm, which is based on a posteriori error estimators. At that stage a comparison of different estimations is performed. Additionally a method to effectively estimate the error in local quantities derived from the solution, so-called "functional outputs", is developed by transferring the dual weighted residual method to mixed finite elements. For a model problem we present how this method can deliver promising results even when standard error estimator fail completely to reduce the error in an iterative mesh refinement process.

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The subject of this thesis is in the area of Applied Mathematics known as Inverse Problems. Inverse problems are those where a set of measured data is analysed in order to get as much information as possible on a model which is assumed to represent a system in the real world. We study two inverse problems in the fields of classical and quantum physics: QCD condensates from tau-decay data and the inverse conductivity problem. Despite a concentrated effort by physicists extending over many years, an understanding of QCD from first principles continues to be elusive. Fortunately, data continues to appear which provide a rather direct probe of the inner workings of the strong interactions. We use a functional method which allows us to extract within rather general assumptions phenomenological parameters of QCD (the condensates) from a comparison of the time-like experimental data with asymptotic space-like results from theory. The price to be paid for the generality of assumptions is relatively large errors in the values of the extracted parameters. Although we do not claim that our method is superior to other approaches, we hope that our results lend additional confidence to the numerical results obtained with the help of methods based on QCD sum rules. EIT is a technology developed to image the electrical conductivity distribution of a conductive medium. The technique works by performing simultaneous measurements of direct or alternating electric currents and voltages on the boundary of an object. These are the data used by an image reconstruction algorithm to determine the electrical conductivity distribution within the object. In this thesis, two approaches of EIT image reconstruction are proposed. The first is based on reformulating the inverse problem in terms of integral equations. This method uses only a single set of measurements for the reconstruction. The second approach is an algorithm based on linearisation which uses more then one set of measurements. A promising result is that one can qualitatively reconstruct the conductivity inside the cross-section of a human chest. Even though the human volunteer is neither two-dimensional nor circular, such reconstructions can be useful in medical applications: monitoring for lung problems such as accumulating fluid or a collapsed lung and noninvasive monitoring of heart function and blood flow.

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This research work presents the design and implementation of a FFT pruning block, which is an extension to the FFT core for OFDM demodulation, enabling run-time 8 pruning of the FFT algorithm, without any restrictions on the distribution pattern of the active/inactive sub-carriers. The design and implementation of FFT processor core is not the part of this work. The whole design was prototyped on an ALTERA STRATIX V FPGA to evaluate the performance of the pruning engine. Synthesis and simulation results showed that the logic overhead introduced by the pruning block is limited to a 10% of the total resources utilization. Moreover, in presence of a medium-high scattering of the sub-carriers, power and energy consumption of the FFT core were reduced by a 30% factor.

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In this thesis, we extend some ideas of statistical physics to describe the properties of human mobility. By using a database containing GPS measures of individual paths (position, velocity and covered space at a spatial scale of 2 Km or a time scale of 30 sec), which includes the 2% of the private vehicles in Italy, we succeed in determining some statistical empirical laws pointing out "universal" characteristics of human mobility. Developing simple stochastic models suggesting possible explanations of the empirical observations, we are able to indicate what are the key quantities and cognitive features that are ruling individuals' mobility. To understand the features of individual dynamics, we have studied different aspects of urban mobility from a physical point of view. We discuss the implications of the Benford's law emerging from the distribution of times elapsed between successive trips. We observe how the daily travel-time budget is related with many aspects of the urban environment, and describe how the daily mobility budget is then spent. We link the scaling properties of individual mobility networks to the inhomogeneous average durations of the activities that are performed, and those of the networks describing people's common use of space with the fractional dimension of the urban territory. We study entropy measures of individual mobility patterns, showing that they carry almost the same information of the related mobility networks, but are also influenced by a hierarchy among the activities performed. We discover that Wardrop's principles are violated as drivers have only incomplete information on traffic state and therefore rely on knowledge on the average travel-times. We propose an assimilation model to solve the intrinsic scattering of GPS data on the street network, permitting the real-time reconstruction of traffic state at a urban scale.

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DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.

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The development of a multibody model of a motorbike engine cranktrain is presented in this work, with an emphasis on flexible component model reduction. A modelling methodology based upon the adoption of non-ideal joints at interface locations, and the inclusion of component flexibility, is developed: both are necessary tasks if one wants to capture dynamic effects which arise in lightweight, high-speed applications. With regard to the first topic, both a ball bearing model and a journal bearing model are implemented, in order to properly capture the dynamic effects of the main connections in the system: angular contact ball bearings are modelled according to a five-DOF nonlinear scheme in order to grasp the crankshaft main bearings behaviour, while an impedance-based hydrodynamic bearing model is implemented providing an enhanced operation prediction at the conrod big end locations. Concerning the second matter, flexible models of the crankshaft and the connecting rod are produced. The well-established Craig-Bampton reduction technique is adopted as a general framework to obtain reduced model representations which are suitable for the subsequent multibody analyses. A particular component mode selection procedure is implemented, based on the concept of Effective Interface Mass, allowing an assessment of the accuracy of the reduced models prior to the nonlinear simulation phase. In addition, a procedure to alleviate the effects of modal truncation, based on the Modal Truncation Augmentation approach, is developed. In order to assess the performances of the proposed modal reduction schemes, numerical tests are performed onto the crankshaft and the conrod models in both frequency and modal domains. A multibody model of the cranktrain is eventually assembled and simulated using a commercial software. Numerical results are presented, demonstrating the effectiveness of the implemented flexible model reduction techniques. The advantages over the conventional frequency-based truncation approach are discussed.

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Traditionally, the study of internal combustion engines operation has focused on the steady-state performance. However, the daily driving schedule of automotive engines is inherently related to unsteady conditions. There are various operating conditions experienced by (diesel) engines that can be classified as transient. Besides the variation of the engine operating point, in terms of engine speed and torque, also the warm up phase can be considered as a transient condition. Chapter 2 has to do with this thermal transient condition; more precisely the main issue is the performance of a Selective Catalytic Reduction (SCR) system during cold start and warm up phases of the engine. The proposal of the underlying work is to investigate and identify optimal exhaust line heating strategies, to provide a fast activation of the catalytic reactions on SCR. Chapters 3 and 4 focus the attention on the dynamic behavior of the engine, when considering typical driving conditions. The common approach to dynamic optimization involves the solution of a single optimal-control problem. However, this approach requires the availability of models that are valid throughout the whole engine operating range and actuator ranges. In addition, the result of the optimization is meaningful only if the model is very accurate. Chapter 3 proposes a methodology to circumvent those demanding requirements: an iteration between transient measurements to refine a purpose-built model and a dynamic optimization which is constrained to the model validity region. Moreover all numerical methods required to implement this procedure are presented. Chapter 4 proposes an approach to derive a transient feedforward control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient.

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This thesis reports on the creation and analysis of many-body states of interacting fermionic atoms in optical lattices. The realized system can be described by the Fermi-Hubbard hamiltonian, which is an important model for correlated electrons in modern condensed matter physics. In this way, ultra-cold atoms can be utilized as a quantum simulator to study solid state phenomena. The use of a Feshbach resonance in combination with a blue-detuned optical lattice and a red-detuned dipole trap enables an independent control over all relevant parameters in the many-body hamiltonian. By measuring the in-situ density distribution and doublon fraction it has been possible to identify both metallic and insulating phases in the repulsive Hubbard model, including the experimental observation of the fermionic Mott insulator. In the attractive case, the appearance of strong correlations has been detected via an anomalous expansion of the cloud that is caused by the formation of non-condensed pairs. By monitoring the in-situ density distribution of initially localized atoms during the free expansion in a homogeneous optical lattice, a strong influence of interactions on the out-of-equilibrium dynamics within the Hubbard model has been found. The reported experiments pave the way for future studies on magnetic order and fermionic superfluidity in a clean and well-controlled experimental system.

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The composition of the atmosphere is frequently perturbed by the emission of gaseous and particulate matter from natural as well as anthropogenic sources. While the impact of trace gases on the radiative forcing of the climate is relatively well understood the role of aerosol is far more uncertain. Therefore, the study of the vertical distribution of particulate matter in the atmosphere and its chemical composition contribute valuable information to bridge this gap of knowledge. The chemical composition of aerosol reveals information on properties such as radiative behavior and hygroscopicity and therefore cloud condensation or ice nucleus potential. rnThis thesis focuses on aerosol pollution plumes observed in 2008 during the POLARCAT (Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols, and Transport) campaign over Greenland in June/July and CONCERT (Contrail and Cirrus Experiment) campaign over Central and Western Europe in October/November. Measurements were performed with an Aerodyne compact time-of-flight aerosol mass spectrometer (AMS) capable of online size-resolved chemical characterization of non-refractory submicron particles. In addition, the origins of pollution plumes were determined by means of modeling tools. The characterized pollution episodes originated from a large variety of sources and were encountered at distinct altitudes. They included pure natural emissions from two volcanic eruptions in 2008. By the time of detection over Western Europe between 10 and 12 km altitude the plume was about 3 months old and composed to 71 % of particulate sulfate and 21 % of carbonaceous compounds. Also, biomass burning (BB) plumes were observed over Greenland between 4 and 7 km altitude (free troposphere) originating from Canada and East Siberia. The long-range transport took roughly one and two weeks, respectively. The aerosol was composed of 78 % organic matter and 22 % particulate sulfate. Some Canadian and all Siberian BB plumes were mixed with anthropogenic emissions from fossil fuel combustion (FF) in North America and East Asia. It was found that the contribution of particulate sulfate increased with growing influences from anthropogenic activity and Asia reaching up to 37 % after more than two weeks of transport time. The most exclusively anthropogenic emission source probed in the upper troposphere was engine exhaust from commercial aircraft liners over Germany. However, in-situ characterization of this aerosol type during aircraft chasing was not possible. All long-range transport aerosol was found to have an O:C ratio close to or greater than 1 implying that low-volatility oxygenated organic aerosol was present in each case despite the variety of origins and the large range in age from 3 to 100 days. This leads to the conclusion that organic particulate matter reaches a final and uniform state of oxygenation after at least 3 days in the free troposphere. rnExcept for aircraft exhaust all emission sources mentioned above are surface-bound and thus rely on different types of vertical transport mechanisms, such as direct high altitude injection in the case of a volcanic eruption, or severe BB, or uplift by convection, to reach higher altitudes where particles can travel long distances before removal mainly caused by cloud scavenging. A lifetime for North American mixed BB and FF aerosol of 7 to 11 days was derived. This in consequence means that emission from surface point sources, e.g. volcanoes, or regions, e.g. East Asia, do not only have a relevant impact on the immediate surroundings but rather on a hemispheric scale including such climate sensitive zones as the tropopause or the Arctic.

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In this thesis, the phenomenology of the Randall-Sundrum setup is investigated. In this context models with and without an enlarged SU(2)_L x SU(2)_R x U(1)_X x P_{LR} gauge symmetry, which removes corrections to the T parameter and to the Z b_L \bar b_L coupling, are compared with each other. The Kaluza-Klein decomposition is formulated within the mass basis, which allows for a clear understanding of various model-specific features. A complete discussion of tree-level flavor-changing effects is presented. Exact expressions for five dimensional propagators are derived, including Yukawa interactions that mediate flavor-off-diagonal transitions. The symmetry that reduces the corrections to the left-handed Z b \bar b coupling is analyzed in detail. In the literature, Randall-Sundrum models have been used to address the measured anomaly in the t \bar t forward-backward asymmetry. However, it will be shown that this is not possible within a natural approach to flavor. The rare decays t \to cZ and t \to ch are investigated, where in particular the latter could be observed at the LHC. A calculation of \Gamma_{12}^{B_s} in the presence of new physics is presented. It is shown that the Randall-Sundrum setup allows for an improved agreement with measurements of A_{SL}^s, S_{\psi\phi}, and \Delta\Gamma_s. For the first time, a complete one-loop calculation of all relevant Higgs-boson production and decay channels in the custodial Randall-Sundrum setup is performed, revealing a sensitivity to large new-physics scales at the LHC.

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Theories and numerical modeling are fundamental tools for understanding, optimizing and designing present and future laser-plasma accelerators (LPAs). Laser evolution and plasma wave excitation in a LPA driven by a weakly relativistically intense, short-pulse laser propagating in a preformed parabolic plasma channel, is studied analytically in 3D including the effects of pulse steepening and energy depletion. At higher laser intensities, the process of electron self-injection in the nonlinear bubble wake regime is studied by means of fully self-consistent Particle-in-Cell simulations. Considering a non-evolving laser driver propagating with a prescribed velocity, the geometrical properties of the non-evolving bubble wake are studied. For a range of parameters of interest for laser plasma acceleration, The dependence of the threshold for self-injection in the non-evolving wake on laser intensity and wake velocity is characterized. Due to the nonlinear and complex nature of the Physics involved, computationally challenging numerical simulations are required to model laser-plasma accelerators operating at relativistic laser intensities. The numerical and computational optimizations, that combined in the codes INF&RNO and INF&RNO/quasi-static give the possibility to accurately model multi-GeV laser wakefield acceleration stages with present supercomputing architectures, are discussed. The PIC code jasmine, capable of efficiently running laser-plasma simulations on Graphics Processing Units (GPUs) clusters, is presented. GPUs deliver exceptional performance to PIC codes, but the core algorithms had to be redesigned for satisfying the constraints imposed by the intrinsic parallelism of the architecture. The simulation campaigns, run with the code jasmine for modeling the recent LPA experiments with the INFN-FLAME and CNR-ILIL laser systems, are also presented.