11 resultados para DYNAMICS SIMULATIONS

em AMS Tesi di Laurea - Alm@DL - Università di Bologna


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For 40 years, at the University of Bologna, a group of researchers coordinated by professor Claudio Zannoni has been studying liquid crystals by employing computational techniques. They have developed effective models of these interesting, and still far from being completely understood, systems. They were able to reproduce with simulations important features of some liquid crystal molecules, such as transition temperature. Then they focused their attention on the interactions that these molecules have with different kinds of surface, and how these interactions affect the alignment of liquid crystals. The group studied the behaviour of liquid crystals in contact with different kinds of surfaces, from silica, either amorphous and crystalline, to organic self assembled monolayers (SAMs) and even some common polymers, such as polymethylmethacrylate (PMMA) and polystyrene (PS). Anyway, a library of typical surfaces is still far from being complete, and a lot of work must be done to investigate the cases which have not been analyzed yet. A hole that must be filled is represented by polydimethylsiloxane (PDMS), a polymer on which the interest of industry has enormously grown up in the last years, thanks to its peculiar features, allowing it to be employed in many fields of applications. It has been observed experimentally that PDMS causes 4-cyano-4’-pentylbiphenyl (well known as 5CB), one of the most common liquid crystal molecules, to align homeotropically (i.e. perpendicular) with respect to a surface made of this polymer. Even though some hypothesis have been presented to rationalize the effect, a clear explanation of this phenomenon has not been given yet. This dissertation shows the work I did during my internship in the group of professor Zannoni. The challenge that I had to tackle was to investigate, via Molecular Dynamics (MD) simulations, the reasons of 5CB homeotropic alignment on a PDMS surface, as the group had previously done for other surfaces.

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The aim of my thesis is to parallelize the Weighting Histogram Analysis Method (WHAM), which is a popular algorithm used to calculate the Free Energy of a molucular system in Molecular Dynamics simulations. WHAM works in post processing in cooperation with another algorithm called Umbrella Sampling. Umbrella Sampling has the purpose to add a biasing in the potential energy of the system in order to force the system to sample a specific region in the configurational space. Several N independent simulations are performed in order to sample all the region of interest. Subsequently, the WHAM algorithm is used to estimate the original system energy starting from the N atomic trajectories. The parallelization of WHAM has been performed through CUDA, a language that allows to work in GPUs of NVIDIA graphic cards, which have a parallel achitecture. The parallel implementation may sensibly speed up the WHAM execution compared to previous serial CPU imlementations. However, the WHAM CPU code presents some temporal criticalities to very high numbers of interactions. The algorithm has been written in C++ and executed in UNIX systems provided with NVIDIA graphic cards. The results were satisfying obtaining an increase of performances when the model was executed on graphics cards with compute capability greater. Nonetheless, the GPUs used to test the algorithm is quite old and not designated for scientific calculations. It is likely that a further performance increase will be obtained if the algorithm would be executed in clusters of GPU at high level of computational efficiency. The thesis is organized in the following way: I will first describe the mathematical formulation of Umbrella Sampling and WHAM algorithm with their apllications in the study of ionic channels and in Molecular Docking (Chapter 1); then, I will present the CUDA architectures used to implement the model (Chapter 2); and finally, the results obtained on model systems will be presented (Chapter 3).

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In this work we have studied, by means of Molecular Dynamics simulations, the process of denaturation and self-assembly of short oligonucleotides. Supramolecular ordering of DNA short strands is a promising field which is constantly enriched with new findings. Examples are provided by micellar and fibrils formations and due to the selectivity of DNA bindings, "intelligent" devices have been developed to perform simple logic operations. It is worth to notice that computer simulations of these DNA nanosystems would complement experiments with detailed insight into processes involved in self-assembly. In order to obtain an accurate description of the interactions involved in the complex structure of DNA we used oxDNA, a coarse-grained model developed by Ouldridge. We simulated the melting transition of 4, 6, and 8 base pair sequences. Sequence and length dependence were analyzed, specifically we compared thermodynamic parameters DeltaH, DeltaS and the melting temperature with literature results. Moreover, we have attempted to reproduce liquid crystal ordering of the ultrashort sequence GCCG at relatively high saline concentration, until now only experimentally observed in Bellini's works. We found that our simple model successfully reproduces the experimental phase sequence (isotropic, nematic, columnar) at T= 5 °C as a function of oligonucleotide concentration, and we fully characterized the microscopic structure of the three phases.

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In questa tesi viene descritto lo studio delle fasi liquido-cristalline del 4-n-ottil-4-cianobifenile eseguito tramite simulazioni al calcolatore molecular dynamics, sia per campioni bulk che per film smectici sottili. Impiegando un campo di forze "molecular mechanics" precedentemente usato con successo per studiare sistemi composti da 250 molecole della serie degli n-cianobifenili (nCB, con n pari a 4-8 atomi di carbonio nella catena alifatica), si è simulato il comportamento di un sistema bulk di 750 molecole e di un film smectico di 1500 molecole. Nel primo caso, sottoponendo il campione a un graduale raffreddamento, si è osservata la formazione spontanea di fasi ordinate quali quella nematica e quella smectica. Nel secondo caso, invece, si è studiata l'influenza dell'interfaccia con il vuoto sull'ordine posizionale e orientazionale di film sottili di diverso spessore e temperatura. Si sono confrontate le proprietà di entrambi i sistemi simulati con i dati sperimentali disponibili in letteratura, confermando la bontà del modello nel riprodurre fedelmente le caratteristiche dei campioni reali.

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Liquid crystals (LCs) are an interesting class of soft condensed matter systems characterized by an unusual combination of fluidity and long-range order, mainly known for their applications in displays (LCDs). However, the interest in LC continues to grow pushed by their application in new technologies in medicine, optical imaging, micro and nano technologies etc. In LCDs uniaxial alignment of LCs is mainly achieved by a rubbing process. During this treatment, the surfaces of polymer coated display substrates are rubbed in one direction by a rotating cylinder covered with a rubbing cloth. Basically, LC alignment involves two possible aligning directions: uniaxial planar (homogeneous) and vertical (homeotropic) to the display substrate. An interesting unresolved question concerning LCs regards the origin of their alignment on rubbed surfaces, and in particular on the polymeric ones used in the display industry. Most studies have shown that LCs on the surface of the rubbed polymer film layer are lying parallel to the rubbing direction. In these systems, micrometric grooves are generated on the film surface along the rubbing direction and also the polymer chains are stretched in this direction. Both the parallel aligned microgrooves and the polymer chains at the film surface may play a role in the LC alignment and it is not easy to quantify the effect of each contribution. The work described in this thesis is an attempt to find new microscopic evidences on the origin of LC alignment on polymeric surfaces through molecular dynamics (MD) simulations, which allow the investigation of the phenomenon with atomic detail. The importance of the arrangement of the polymeric chains in LCs alignment was studied by performing MD simulations of a thin film of a typical nematic LC, 4-cyano-4’-pentylbiphenyl (5CB), in contact with two different polymers: poly(methyl methacrylate)(PMMA) and polystyrene (PS). At least four factors are believed to influence the LC alignment: 1. the interactions of LCs with the backbone vinyl chains; 2. the interactions of LCs with the oriented side groups; 3. the anisotropic interactions of LCs with nanometric grooves; 4. the presence of static surface charges. Here we exclude the effect of microgrooves and of static surface charges from our virtual experiment, by using flat and neutral polymer surfaces, with the aim of isolating the chemical driving factors influencing the alignment of LC phases on polymeric surfaces.

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The last decade has witnessed the establishment of a Standard Cosmological Model, which is based on two fundamental assumptions: the first one is the existence of a new non relativistic kind of particles, i. e. the Dark Matter (DM) that provides the potential wells in which structures create, while the second one is presence of the Dark Energy (DE), the simplest form of which is represented by the Cosmological Constant Λ, that sources the acceleration in the expansion of our Universe. These two features are summarized by the acronym ΛCDM, which is an abbreviation used to refer to the present Standard Cosmological Model. Although the Standard Cosmological Model shows a remarkably successful agreement with most of the available observations, it presents some longstanding unsolved problems. A possible way to solve these problems is represented by the introduction of a dynamical Dark Energy, in the form of the scalar field ϕ. In the coupled DE models, the scalar field ϕ features a direct interaction with matter in different regimes. Cosmic voids are large under-dense regions in the Universe devoided of matter. Being nearby empty of matter their dynamics is supposed to be dominated by DE, to the nature of which the properties of cosmic voids should be very sensitive. This thesis work is devoted to the statistical and geometrical analysis of cosmic voids in large N-body simulations of structure formation in the context of alternative competing cosmological models. In particular we used the ZOBOV code (see ref. Neyrinck 2008), a publicly available void finder algorithm, to identify voids in the Halos catalogues extraxted from CoDECS simulations (see ref. Baldi 2012 ). The CoDECS are the largest N-body simulations to date of interacting Dark Energy (DE) models. We identify suitable criteria to produce voids catalogues with the aim of comparing the properties of these objects in interacting DE scenarios to the standard ΛCDM model, at different redshifts. This thesis work is organized as follows: in chapter 1, the Standard Cosmological Model as well as the main properties of cosmic voids are intro- duced. In chapter 2, we will present the scalar field scenario. In chapter 3 the tools, the methods and the criteria by which a voids catalogue is created are described while in chapter 4 we discuss the statistical properties of cosmic voids included in our catalogues. In chapter 5 the geometrical properties of the catalogued cosmic voids are presented by means of their stacked profiles. In chapter 6 we summarized our results and we propose further developments of this work.

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The benthic dinoflagellate O. ovata represents a serious threat for human health and for the ecology of its blooming areas: thanks to its toxicity this microalga has been responsible for several cases of human intoxication and mass mortalities of benthic invertebrates. Although the large number of studies on this dinoflagellate, the mechanisms underpinning O. ovata growth and toxin production are still far to be fully understood. In this work we have enriched the dataset on this species by carrying out a new experiment on an Adriatic O. cf. ovata strain. Data from this experiment (named Beta) and from another comparable experiment previously conducted on the same strain (named Alpha), revealed some interesting aspects of this dinoflagellate: it is able to grow also in a condition of strong intracellular nutrient deficiency (C:P molar ratio > 400; C:N > 25), reaching extremely low values of chlorophyll-a to carbon ratio (0.0004). Was also found a significant inverse relationships (r > -0.7) between cellular toxin to carbon and cellular nutrient to carbon ratios of experiment Alpha. In the light of these result, we hypothesized that in O. cf. ovata nutrient-stress conditions (intended as intracellular nutrient deficiency) can cause: i) an increase in toxin production; ii) a strong decrease in chlorophyll-a synthesis; iii) a lowering of metabolism associated with the formation of a sort of resting stage. We then used a modelling approach to test and critically evaluate these hypotheses in a mechanistic way: newly developed formulation describing toxin production and fate, and ad hoc changes in the already existent formulations describing chlorophyll synthesis, rest respiration, and mortality, have been incorporated in a simplified version of the European Regional Seas Ecosystem Model (ERSEM), together with a new ad hoc parameterization. The adapted model was able to accurately reproduce many of the trends observed in the Alpha experiment, allowing us to support our hypotheses. Instead the simulations of the experiment Beta were not fully satisfying in quantitative terms. We explained this gap with the presumed different physiological behaviors between the algae of the two experiments, due to the different pre-experimental periods of acclimation: the model was not able to reproduce acclimation processes in its simulations of the experiment Beta. Thus we attempt to simulate the acclimation of the algae to nutrient-stress conditions by manual intervention on some parameters of nutrient-stress thresholds, but we received conflicting results. Further studies are required to shed light on this interesting aspect. In this work we also improve the range of applicability of a state of the art marine biogeochemical model (ERSEM) by implementing in it an ecological relevant process such as the production of toxic compounds.

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Feedback from the most massive components of a young stellar cluster deeply affects the surrounding ISM driving an expanding over-pressured hot gas cavity in it. In spiral galaxies these structures may have sufficient energy to break the disk and eject large amount of material into the halo. The cycling of this gas, which eventually will fall back onto the disk, is known as galactic fountains. We aim at better understanding the dynamics of such fountain flow in a Galactic context, frame the problem in a more dynamic environment possibly learning about its connection and regulation to the local driving mechanism and understand its role as a metal diffusion channel. The interaction of the fountain with a hot corona is hereby analyzed, trying to understand the properties and evolution of the extraplanar material. We perform high resolution hydrodynamical simulations with the moving-mesh code AREPO to model the multi-phase ISM of a Milky Way type galaxy. A non-equilibrium chemical network is included to self consistently follow the evolution of the main coolants of the ISM. Spiral arm perturbations in the potential are considered so that large molecular gas structures are able to dynamically form here, self shielded from the interstellar radiation field. We model the effect of SN feedback from a new-born stellar cluster inside such a giant molecular cloud, as the driving force of the fountain. Passive Lagrangian tracer particles are used in conjunction to the SN energy deposition to model and study diffusion of freshly synthesized metals. We find that both interactions with hot coronal gas and local ISM properties and motions are equally important in shaping the fountain. We notice a bimodal morphology where most of the ejected gas is in a cold $10^4$ K clumpy state while the majority of the affected volume is occupied by a hot diffuse medium. While only about 20\% of the produced metals stay local, most of them quickly diffuse through this hot regime to great scales.

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Turbulent plasmas inside tokamaks are modeled and studied using guiding center theory, applied to charged test particles, in a Hamiltonian framework. The equations of motion for the guiding center dynamics, under the conditions of a constant and uniform magnetic field and turbulent electrostatic field are derived by averaging over the fast gyroangle, for the first and second order in the guiding center potential, using invertible changes of coordinates such as Lie transforms. The equations of motion are then made dimensionless, exploiting temporal and spatial periodicities of the model chosen for the electrostatic potential. They are implemented numerically in Python. Fast Fourier Transform and its inverse are used. Improvements to the original Python scripts are made, notably the introduction of a power-law curve fitting to account for anomalous diffusion, the possibility to integrate the equations in two steps to save computational time by removing trapped trajectories, and the implementation of multicolored stroboscopic plots to distinguish between trapped and untrapped guiding centers. The post-processing of the results is made in MATLAB. The values and ranges of the parameters chosen for the simulations are selected based on numerous simulations used as feedback tools. In particular, a recurring value for the threshold to detect trapped trajectories is evidenced. Effects of the Larmor radius, the amplitude of the guiding center potential and the intensity of its second order term are studied by analyzing their diffusive regimes, their stroboscopic plots and the shape of guiding center potentials. The main result is the identification of cases anomalous diffusion depending on the values of the parameters (mostly the Larmor radius). The transitions between diffusive regimes are identified. The presence of highways for the super-diffusive trajectories are unveiled. The influence of the charge on these transitions from diffusive to ballistic behaviors is analyzed.

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In this work, integro-differential reaction-diffusion models are presented for the description of the temporal and spatial evolution of the concentrations of Abeta and tau proteins involved in Alzheimer's disease. Initially, a local model is analysed: this is obtained by coupling with an interaction term two heterodimer models, modified by adding diffusion and Holling functional terms of the second type. We then move on to the presentation of three nonlocal models, which differ according to the type of the growth (exponential, logistic or Gompertzian) considered for healthy proteins. In these models integral terms are introduced to consider the interaction between proteins that are located at different spatial points possibly far apart. For each of the models introduced, the determination of equilibrium points with their stability and a study of the clearance inequalities are carried out. In addition, since the integrals introduced imply a spatial nonlocality in the models exhibited, some general features of nonlocal models are presented. Afterwards, with the aim of developing simulations, it is decided to transfer the nonlocal models to a brain graph called connectome. Therefore, after setting out the construction of such a graph, we move on to the description of Laplacian and convolution operations on a graph. Taking advantage of all these elements, we finally move on to the translation of the continuous models described above into discrete models on the connectome. To conclude, the results of some simulations concerning the discrete models just derived are presented.

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Since the majority of the population of the world lives in cities and that this number is expected to increase in the next years, one of the biggest challenges of the research is the determination of the risk deriving from high temperatures experienced in urban areas, together with improving responses to climate-related disasters, for example by introducing in the urban context vegetation or built infrastructures that can improve the air quality. In this work, we will investigate how different setups of the boundary and initial conditions set on an urban canyon generate different patterns of the dispersion of a pollutant. To do so we will exploit the low computational cost of Reynolds-Averaged Navier-Stokes (RANS) simulations to reproduce the dynamics of an infinite array of two-dimensional square urban canyons. A pollutant is released at the street level to mimic the presence of traffic. RANS simulations are run using the k-ɛ closure model and vertical profiles of significant variables of the urban canyon, namely the velocity, the turbulent kinetic energy, and the concentration, are represented. This is done using the open-source software OpenFOAM and modifying the standard solver simpleFoam to include the concentration equation and the temperature by introducing a buoyancy term in the governing equations. The results of the simulation are validated with experimental results and products of Large-Eddy Simulations (LES) from previous works showing that the simulation is able to reproduce all the quantities under examination with satisfactory accuracy. Moreover, this comparison shows that despite LES are known to be more accurate albeit more expensive, RANS simulations represent a reliable tool if a smaller computational cost is needed. Overall, this work exploits the low computational cost of RANS simulations to produce multiple scenarios useful to evaluate how the dispersion of a pollutant changes by a modification of key variables, such as the temperature.