5 resultados para Brownian Dynamics Simulation

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


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Capire come modellare l'attività del cervello a riposo, resting state, è il primo passo necessario per avvicinarsi a una reale comprensione della dinamica cerebrale. Sperimentalmente si osserva che, quando il cervello non è soggetto a stimoli esterni, particolari reti di regioni cerebrali presentano un'attività neuronale superiore alla media. Nonostante gli sforzi dei ricercatori, non è ancora chiara la relazione che sussiste tra le connessioni strutturali e le connessioni funzionali del sistema cerebrale a riposo, organizzate nella matrice di connettività funzionale. Recenti studi sperimentali mostrano la natura non stazionaria della connettività funzionale in disaccordo con i modelli in letteratura. Il modello implementato nella presente tesi per simulare l'evoluzione temporale del network permette di riprodurre il comportamento dinamico della connettività funzionale. Per la prima volta in questa tesi, secondo i lavori a noi noti, un modello di resting state è implementato nel cervello di un topo. Poco è noto, infatti, riguardo all'architettura funzionale su larga scala del cervello dei topi, nonostante il largo utilizzo di tale sistema nella modellizzazione dei disturbi neurologici. Le connessioni strutturali utilizzate per definire la topologia della rete neurale sono quelle ottenute dall'Allen Institute for Brain Science. Tale strumento fornisce una straordinaria opportunità per riprodurre simulazioni realistiche, poiché, come affermato nell'articolo che presenta tale lavoro, questo connettoma è il più esauriente disponibile, ad oggi, in ogni specie vertebrata. I parametri liberi del modello sono stati scelti in modo da inizializzare il sistema nel range dinamico ottimale per riprodurre il comportamento dinamico della connettività funzionale. Diverse considerazioni e misure sono state effettuate sul segnale BOLD simulato per meglio comprenderne la natura. L'accordo soddisfacente fra i centri funzionali calcolati nel network cerebrale simulato e quelli ottenuti tramite l'indagine sperimentale di Mechling et al., 2014 comprovano la bontà del modello e dei metodi utilizzati per analizzare il segnale simulato.

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The Gulf of Aqaba represents a small scale, easy to access, regional analogue of larger oceanic oligotrophic systems. In this Gulf, the seasonal cycles of stratification and mixing drives the seasonal phytoplankton dynamics. In summer and fall, when nutrient concentrations are very low, Prochlorococcus and Synechococcus are more abundant in the surface water. This two populations are exposed to phosphate limitation. During winter mixing, when nutrient concentrations are high, Chlorophyceae and Cryptophyceae are dominant but scarce or absent during summer. In this study it was tried to develop a simulation model based on historical data to predict the phytoplankton dynamics in the northern Gulf of Aqaba. The purpose is to understand what forces operate, and how, to determine the phytoplankton dynamics in this Gulf. To make the models data sampled in two different sampling station (Fish Farm Station and Station A) were used. The data of chemical, biological and physical factors, are available from 14th January 2007 to 28th December 2009. The Fish Farm Station point was near a Fish Farm that was operational until 17th June 2008, complete closure date of the Fish Farm, about halfway through the total sampling time. The Station A sampling point is about 13 Km away from the Fish Farm Station. To build the model, the MATLAB software was used (version 7.6.0.324 R2008a), in particular a tool named Simulink. The Fish Farm Station models shows that the Fish Farm activity has altered the nutrient concentrations and as a consequence the normal phytoplankton dynamics. Despite the distance between the two sampling stations, there might be an influence from the Fish Farm activities also in the Station A ecosystem. The models about this sampling station shows that the Fish Farm impact appears to be much lower than the impact in the Fish Farm Station, because the phytoplankton dynamics appears to be driven mainly by the seasonal mixing cycle.

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The research performed in the framework of this Master Thesis has been directly inspired by the recent work of an organometallic research group led by Professor Maria Cristina Cassani on a topic related to the structures, dynamics and catalytic activity of N-heterocyclic carbene-amide rhodium(I) complexes1. A series of [BocNHCH2CH2ImR]X (R = Me, X = I, 1a’; R = Bz, X = Br, 1b’; R = trityl, X = Cl, 1c’) amide-functionalized imidazolium salts bearing increasingly bulky N-alkyl substituents were synthetized and characterized. Subsequently, these organic precursors were employed in the synthesis of silver(I) complexes as intermediate compounds on a way to rhodium(I) complexes [Rh(NBD)X(NHC)] (NHC = 1-(2-NHBoc-ethyl)-3-R-imidazolin-2-ylidene; X = Cl, R = Me (3a’), R = Bz (3b’), R = trityl (3c’); X = I, R = Me (4a’)). VT NMR studies of these complexes revealed a restricted rotation barriers about the metal-carbene bond. However, while the rotation barriers calculated for the complexes in which R = Me, Bz (3a’,b’ and 4a) matched the experimental values, this was not true in the trityl case 3c’, where the experimental value was very similar to that obtained for compound 3b’ and much smaller with respect to the calculated one. In addition, the energy barrier derived for 3c’ from line shape simulation showed a strong dependence on the temperature, while the barriers measured for 3a’,b’ did not show this effect. In view of these results and in order to establish the reasons for the previously found inconsistency between calculated and experimental thermodynamic data, the first objective of this master thesis was the preparation of a series of rhodium(I) complexes [Rh(NBD)X(NHC)] (NHC = 1-benzyl-3-R-imidazolin-2-ylidene; X = Cl, R = Me, Bz, trityl, tBu), containing the benzyl substituent as a chiral probe, followed by full characterization. The second objective of this work was to investigate the catalytic activity of the new rhodium compounds in the hydrosilylation of terminal alkynes for comparison purposes with the reported complexes. Another purpose of this work was to employ the prepared N-heterocyclic ligands in the synthesis of iron(II)-NHC complexes.

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Sub-grid scale (SGS) models are required in order to model the influence of the unresolved small scales on the resolved scales in large-eddy simulations (LES), the flow at the smallest scales of turbulence. In the following work two SGS models are presented and deeply analyzed in terms of accuracy through several LESs with different spatial resolutions, i.e. grid spacings. The first part of this thesis focuses on the basic theory of turbulence, the governing equations of fluid dynamics and their adaptation to LES. Furthermore, two important SGS models are presented: one is the Dynamic eddy-viscosity model (DEVM), developed by \cite{germano1991dynamic}, while the other is the Explicit Algebraic SGS model (EASSM), by \cite{marstorp2009explicit}. In addition, some details about the implementation of the EASSM in a Pseudo-Spectral Navier-Stokes code \cite{chevalier2007simson} are presented. The performance of the two aforementioned models will be investigated in the following chapters, by means of LES of a channel flow, with friction Reynolds numbers $Re_\tau=590$ up to $Re_\tau=5200$, with relatively coarse resolutions. Data from each simulation will be compared to baseline DNS data. Results have shown that, in contrast to the DEVM, the EASSM has promising potentials for flow predictions at high friction Reynolds numbers: the higher the friction Reynolds number is the better the EASSM will behave and the worse the performances of the DEVM will be. The better performance of the EASSM is contributed to the ability to capture flow anisotropy at the small scales through a correct formulation for the SGS stresses. Moreover, a considerable reduction in the required computational resources can be achieved using the EASSM compared to DEVM. Therefore, the EASSM combines accuracy and computational efficiency, implying that it has a clear potential for industrial CFD usage.

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Recent studies found that soil-atmosphere coupling features, through soil moisture, have been crucial to simulate well heat waves amplitude, duration and intensity. Moreover, it was found that soil moisture depletion both in Winter and Spring anticipates strong heat waves during the Summer. Irrigation in geophysical studies can be intended as an anthropogenic forcing to the soil-moisture, besides changes in land proprieties. In this study, the irrigation was add to a LAM hydrostatic model (BOLAM) and coupled with the soil. The response of the model to irrigation perturbation is analyzed during a dry Summer season. To identify a dry Summer, with overall positive temperature anomalies, an extensive climatological characterization of 2015 was done. The method included a statistical validation on the reference period distribution used to calculate the anomalies. Drought conditions were observed during Summer 2015 and previous seasons, both on the analyzed region and the Alps. Moreover July was characterized as an extreme event for the referred distribution. The numerical simulation consisted on the summer season of 2015 and two run: a control run (CTR), with the soil coupling and a perturbed run (IPR). The perturbation consists on a mask of land use created from the Cropland FAO dataset, where an irrigation water flux of 3 mm/day was applied from 6 A.M. to 9 A.M. every day. The results show that differences between CTR and IPR has a strong daily cycle. The main modifications are on the air masses proprieties, not on to the dynamics. However, changes in the circulation at the boundaries of the Po Valley are observed, and a diagnostic spatial correlation of variable differences shows that soil moisture perturbation explains well the variation observed in the 2 meters height temperature and in the latent heat fluxes.On the other hand, does not explain the spatial shift up and downslope observed during different periods of the day. Given the results, irrigation process affects the atmospheric proprieties on a larger scale than the irrigation, therefore it is important in daily forecast, particularly during hot and dry periods.