937 resultados para FEA simulations
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In this work, we report a 20-ns constant pressure molecular dynamics simulation of prilocaine (PLC), in amine-amide local anesthetic, in a hydrated liquid crystal bilayer of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine. The partition of PLC induces the lateral expansion of the bilayer and a concomitant contraction in its thickness. PLC molecules are preferentially found in the hydrophobic acyl chains region, with a maximum probability at similar to 12 angstrom from the center of the bilayer (between the C(4) and C(5) methylene groups). A decrease in the acyl chain segmental order parameter, vertical bar S-CD vertical bar, compared to neat bilayers, is found, in good agreement with experimental H-2-NMR studies. The decrease in vertical bar S-CD vertical bar induced by PLC is attributed to a larger accessible volume per lipid in the acyl chain region. (C) 2008 Wiley Periodicals, Inc.
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Various mechanisms have been proposed to explain extreme waves or rogue waves in an oceanic environment including directional focusing, dispersive focusing, wave-current interaction, and nonlinear modulational instability. The Benjamin-Feir instability (nonlinear modulational instability), however, is considered to be one of the primary mechanisms for rogue-wave occurrence. The nonlinear Schrodinger equation is a well-established approximate model based on the same assumptions as required for the derivation of the Benjamin-Feir theory. Solutions of the nonlinear Schrodinger equation, including new rogue-wave type solutions are presented in the author's dissertation work. The solutions are obtained by using a predictive eigenvalue map based predictor-corrector procedure developed by the author. Features of the predictive map are explored and the influences of certain parameter variations are investigated. The solutions are rescaled to match the length scales of waves generated in a wave tank. Based on the information provided by the map and the details of physical scaling, a framework is developed that can serve as a basis for experimental investigations into a variety of extreme waves as well localizations in wave fields. To derive further fundamental insights into the complexity of extreme wave conditions, Smoothed Particle Hydrodynamics (SPH) simulations are carried out on an advanced Graphic Processing Unit (GPU) based parallel computational platform. Free surface gravity wave simulations have successfully characterized water-wave dispersion in the SPH model while demonstrating extreme energy focusing and wave growth in both linear and nonlinear regimes. A virtual wave tank is simulated wherein wave motions can be excited from either side. Focusing of several wave trains and isolated waves has been simulated. With properly chosen parameters, dispersion effects are observed causing a chirped wave train to focus and exhibit growth. By using the insights derived from the study of the nonlinear Schrodinger equation, modulational instability or self-focusing has been induced in a numerical wave tank and studied through several numerical simulations. Due to the inherent dissipative nature of SPH models, simulating persistent progressive waves can be problematic. This issue has been addressed and an observation-based solution has been provided. The efficacy of SPH in modeling wave focusing can be critical to further our understanding and predicting extreme wave phenomena through simulations. A deeper understanding of the mechanisms underlying extreme energy localization phenomena can help facilitate energy harnessing and serve as a basis to predict and mitigate the impact of energy focusing.
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Aim: To investigate the effect of implant-abutment angulation and crown material on stress distribution of central incisors. Finite element method was used to simulate the clinical situation of a maxillary right central incisor restored by two different implant-abutment angulations, 15° and 25°, using two different crown materials (IPS E-Max CAD and zirconia). Methods: Two 3D finite element models were specially prepared for this research simulating the abutment angulations. Commercial engineering CAD/CAM package was used to model crown, implant abutment complex and bone (cortical and spongy) in 3D. Linear static analysis was performed by applying a 178 N oblique load. The obtained results were compared with former experimental results. Results: Implant Von Mises stress level was negligibly changed with increasing abutment angulation. The abutment with higher angulation is mechanically weaker and expected to fail at lower loading in comparison with the steeper one. Similarly, screw used with abutment angulation of 25° will fail at lower (about one-third) load value the failure load of similar screw used with abutment angulated by 15°. Conclusions: Bone (cortical and spongy) is insensitive to crown material. Increasing abutment angulation from 15° to 25°, increases stress on cortical bone by about 20% and reduces it by about 12% on spongy bone. Crown fracture resistance is dramatically reduced by increasing abutment angulation. Zirconia crown showed better performance than E-Max one.
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We describe the application of alchemical free energy methods and coarse-grained models to study two key problems: (i) co-translational protein targeting and insertion to direct membrane proteins to the endoplasmic reticulum for proper localization and folding, (ii) lithium dendrite formation during recharging of lithium metal batteries. We show that conformational changes in the signal recognition particle, a central component of the protein targeting machinery, confer additional specificity during the the recognition of signal sequences. We then develop a three-dimensional coarse-grained model to study the long-timescale dynamics of membrane protein integration at the translocon and a framework for the calculation of binding free energies between the ribosome and translocon. Finally, we develop a coarse-grained model to capture the dynamics of lithium deposition and dissolution at the electrode interface with time-dependent voltages to show that pulse plating and reverse pulse plating methods can mitigate dendrite growth.
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Computational models for the investigation of flows in deformable tubes are developed and implemented in the open source computing environment OpenFOAM. Various simulations for Newtonian and non-Newtonian fluids under various flow conditions are carried out and analyzed. First, simulations are performed to investigate the flow of a shear-thinning, non-Newtonian fluid in a collapsed elastic tube and comparisons are made with experimental data. The fluid is modeled by means of the Bird-Carreau viscosity law. The computational domain of the deformed tube is constructed from data obtained via computer tomography imaging. Comparison of the computed velocity fields with the ultrasound Doppler velocity profile measurements show good agreement, as does the adjusted pressure drop along the tube's axis. Analysis of the shear rates show that the shear-thinning effect of the fluid becomes relevant in the cross-sections with the biggest deformation. The peristaltic motion is simulated by means of upper and lower rollers squeezing the fluid along a tube. Two frames of reference are considered. In the moving frame the computational domain is fixed and the coordinate system is moving with the roller speed, and in the fixed frame the roller is represented by a deforming mesh. Several two-dimensional simulations are carried out for Newtonian and non-Newtonian fluids. The effect of the shear-thinning behavior of the fluid on the transport efficiency is examined. In addition, the influence of the roller speed and the gap width between the rollers on the xxvii transport efficiency is discussed. Comparison with experimental data is also presented and different types of moving waves are implemented. In addition, the influence of the roller speed and the gap width between the rollers on the transport efficiency is discussed. Comparison with experimental data is also presented and different types of moving waves are implemented.
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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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A subfilter-scale (SFS) stress model is developed for large-eddy simulations (LES) and is tested on various benchmark problems in both wall-resolved and wall-modelled LES. The basic ingredients of the proposed model are the model length-scale, and the model parameter. The model length-scale is defined as a fraction of the integral scale of the flow, decoupled from the grid. The portion of the resolved scales (LES resolution) appears as a user-defined model parameter, an advantage that the user decides the LES resolution. The model parameter is determined based on a measure of LES resolution, the SFS activity. The user decides a value for the SFS activity (based on the affordable computational budget and expected accuracy), and the model parameter is calculated dynamically. Depending on how the SFS activity is enforced, two SFS models are proposed. In one approach the user assigns the global (volume averaged) contribution of SFS to the transport (global model), while in the second model (local model), SFS activity is decided locally (locally averaged). The models are tested on isotropic turbulence, channel flow, backward-facing step and separating boundary layer. In wall-resolved LES, both global and local models perform quite accurately. Due to their near-wall behaviour, they result in accurate prediction of the flow on coarse grids. The backward-facing step also highlights the advantage of decoupling the model length-scale from the mesh. Despite the sharply refined grid near the step, the proposed SFS models yield a smooth, while physically consistent filter-width distribution, which minimizes errors when grid discontinuity is present. Finally the model application is extended to wall-modelled LES and is tested on channel flow and separating boundary layer. Given the coarse resolution used in wall-modelled LES, near the wall most of the eddies become SFS and SFS activity is required to be locally increased. The results are in very good agreement with the data for the channel. Errors in the prediction of separation and reattachment are observed in the separated flow, that are somewhat improved with some modifications to the wall-layer model.
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The mechanical behaviour and performance of a ductile iron component is highly dependent on the local variations in solidification conditions during the casting process. Here we show a framework which combine a previously developed closed chain of simulations for cast components with a micro-scale Finite Element Method (FEM) simulation of the behaviour and performance of the microstructure. A casting process simulation, including modelling of solidification and mechanical material characterization, provides the basis for a macro-scale FEM analysis of the component. A critical region is identified to which the micro-scale FEM simulation of a representative microstructure, generated using X-ray tomography, is applied. The mechanical behaviour of the different microstructural phases are determined using a surrogate model based optimisation routine and experimental data. It is discussed that the approach enables a link between solidification- and microstructure-models and simulations of as well component as microstructural behaviour, and can contribute with new understanding regarding the behaviour and performance of different microstructural phases and morphologies in industrial ductile iron components in service.
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In order to advance the knowledge about precipitation development over Madeira island, four rainfall patterns are investigated based on high-resolution numerical simulations performed with the MESO-NH model. The main environmental conditions during these precipitation periods are examined, and important factors leading to significant accumulated precipitation in Madeira are shown. We found that the combination of orographic effect and atmospheric conditions is essential for the establishment of each situation. Under a moist and conditionally unstable atmosphere, convection over the island is triggered, and its location was determined mainly by variations of the ambient flow, which was also associated with different moist Froude numbers. Interestingly, our results showed some similarities with situations discussed in idealized studies. However, the real variations of the atmospheric configuration confirm the complexity of significant precipitation development in mountainous regions. In addition, precipitating systems initially formed over the ocean were simulated reaching the island. The four periods were characterised by different time durations, and the local terrain interacting with the mesoscale circulation was decisive in producing a large part of the precipitation, which concentrated in distinct regions of the island induced by the airflow dynamic.
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High-resolution simulations of high precipitation events with the MESO-NHmodel are presented, and also used to verify that increasing horizontal resolution in zones of complex orography, such as in Madeira island, improve the simulation of the spatial distribution and total precipitation. The simulations succeeded in reproducing the general structure of the cloudy systems over the ocean in the four periods considered of significant accumulated precipitation. The accumulated precipitation over theMadeirawas better represented with the 0.5 km horizontal resolution and occurred under four distinct synoptic situations. Different spatial patterns of the rainfall distribution over the Madeira have been identified
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This work aims at improving the knowledge on fog formation and its evolution in the Alentejo region (Portugal). For this purpose, brief regional fog climatology, essentially based on information from the Beja Air Base meteorological station, was produced and several numerical high resolution simulations were performed using the Meso-NH. The ECOCLIMAP database used to generate the model physiography was improved to include the Alqueva reservoir (~250 km2), filled in 2003. The model results were compared with surface and satellite observations, showing good agreement in terms of fog occurrence and persistence. Various forcing mechanisms for formation, development, and dissipation of fog were identified, confirming the influence of two small mountains that block the moist air from the Atlantic Ocean, preventing the fog from reaching innermost regions. The introduction of the Alqueva large reservoir induces changes in the landscape and environment. The effects of the water vapour addition and of the changes in mass and energy surface fluxes on fog formation and evolution were studied. It was found that the reservoir may have a direct impact on fog formation over the lake and its vicinity. Depending on the large scale meteorological conditions, their influence can be both positive and negative, in terms of spatial coverage and temporal persistence.
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Until recently the dynamical evolution of the interstellar medium (ISM) was simu- lated using collisional ionization equilibrium (CIE) conditions. However, the ISM is a dynamical system, in which the plasma is naturally driven out of equilibrium due to atomic and dynamic processes operating on different timescales. A step forward in the field comprises a multi-fluid approach taking into account the joint thermal and dynamical evolutions of the ISM gas.
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The application of Computational Fluid Dynamics based on the Reynolds-Averaged Navier-Stokes equations to the simulation of bluff body aerodynamics has been thoroughly investigated in the past. Although a satisfactory accuracy can be obtained for some urban physics problems their predictive capability is limited to the mean flow properties, while the ability to accurately predict turbulent fluctuations is recognized to be of fundamental importance when dealing with wind loading and pollution dispersion problems. The need to correctly take into account the flow dynamics when such problems are faced has led researchers to move towards scale-resolving turbulence models such as Large Eddy Simulations (LES). The development and assessment of LES as a tool for the analysis of these problems is nowadays an active research field and represents a demanding engineering challenge. This research work has two objectives. The first one is focused on wind loads assessment and aims to study the capabilities of LES in reproducing wind load effects in terms of internal forces on structural members. This differs from the majority of the existing research, where performance of LES is evaluated only in terms of surface pressures, and is done with a view of adopting LES as a complementary design tools alongside wind tunnel tests. The second objective is the study of LES capabilities in calculating pollutant dispersion in the built environment. The validation of LES in this field is considered to be of the utmost importance in order to conceive healthier and more sustainable cities. In order to validate the numerical setup adopted, a systematic comparison between numerical and experimental data is performed. The obtained results are intended to be used in the drafting of best practice guidelines for the application of LES in the urban physics field with a particular attention to wind load assessment and pollution dispersion problems.
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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 two-metal-ion architecture is a structural feature found in a variety of RNA processing metalloenzymes or ribozymes (RNA-based enzymes), which control the biogenesis and the metabolism of vital RNAs, including non-coding RNAs (ncRNAs). Notably, such ncRNAs are emerging as key players for the regulation of cellular homeostasis, and their altered expression has been often linked to the development of severe human pathologies, from cancer to mental disorders. Accordingly, understanding the biological processing of ncRNAs is foundational for the development of novel therapeutic strategies and tools. Here, we use state-of the-art molecular simulations, complemented with X-ray crystallography and biochemical experiments, to characterize the RNA processing cycle as catalyzed by two two-metal-ion enzymes: the group II intron ribozymes and the RNase H1. We show that multiple and diverse cations are strategically recruited at and timely released from the enzymes’ active site during catalysis. Such a controlled cations’ trafficking leads to the recursive formation and disruption of an extended two-metal ion architecture that is functional for RNA-hydrolysis – from substrate recruitment to product release. Importantly, we found that these cations’ binding sites are conserved among other RNA-processing machineries, including the human spliceosome and CRISPR-Cas systems, suggesting that an evolutionarily-converged catalytic strategy is adopted by these enzymes to process RNA molecules. Thus, our findings corroborate and sensibly extend the current knowledge of two-metal-ion enzymes, and support the design of novel drugs targeting RNA-processing metalloenzymes or ribozymes as well as the rational engineering of novel programmable gene-therapy tools.