126 resultados para Direct Numerical Simulation (Dns)


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The formation of Ge quantum dot arrays by deposition from a low-temperature plasma environment is investigated by kinetic Monte Carlo numerical simulation. It is demonstrated that balancing of the Ge influx from the plasma against surface diffusion provides an effective control of the surface processes and can result in the formation of very small densely packed quantum dots. In the supply-controlled mode, a continuous layer is formed which is then followed by the usual Stranski-Krastanow fragmentation with a nanocluster size of 10 nm. In the diffusion-controlled mode, with the oversupply relative to the surface diffusion rate, nanoclusters with a characteristic size of 3 nm are formed. Higher temperatures change the mode to supply controlled and thus encourage formation of the continuous layer that then fragments into an array of large size. The use of a high rate of deposition, easily accessible using plasma techniques, changes the mode to diffusion controlled and thus encourages formation of a dense array of small nanoislands.

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The growth of carbon nanocone arrays on metal catalyst particles by deposition from a low-temperature plasma is studied by multiscale Monte Carlo/surface diffusion numerical simulation. It is demonstrated that the variation in the degree of ionization of the carbon flux provides an effective control of the growth kinetics of the carbon nanocones, and leads to the formation of more uniform arrays of nanostructures. In the case of zero degree of ionization (neutral gas process), a width of the distribution of nanocone heights reaches 360 nm with the nanocone mean height of 150 nm. When the carbon flux of 75% ionization is used, the width of the distribution of nanocone heights decreases to 100 nm, i.e., by a factor of 3.6. A higher degree of ionization leads to a better uniformity of the metal catalyst saturation and the nanocone growth, thus contributing to the formation of more height-uniform arrays of carbon nanostructures.

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Many properties of single-walled carbon nanotube (SWCNT) arrays are determined by the size and surface coverage of the metal catalyst islands from which they are nucleated. Methods using thermal fragmentation of continuous metal films frequently fail to produce size-uniform islands. Hybrid numerical simulations are used to propose a new approach to controlled self-assembly of Ni islands of the required size and surface coverage using tailored gas-phase generated nanocluster fluxes and adjusted surface temperatures. It is shown that a maximum surface coverage of 0.359 by 0.96-1.02 nm Ni catalyst islands can be achieved at a low surface temperature of 500 K. Optimized growth of Ni catalyst islands can lead to fabrication of size-uniform SWCNT arrays, suitable for numerous nanoelectronic applications. This approach is deterministic and is applicable to a range of nanoassemblies where high surface coverage and island size uniformity are required.

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Angular distribution of microscopic ion fluxes around nanotubes arranged into a dense ordered pattern on the surface of the substrate is studied by means of multiscale numerical simulation. The Monte Carlo technique was used to show that the ion current density is distributed nonuniformly around the carbon nanotubes arranged into a dense rectangular array. The nonuniformity factor of the ion current flux reaches 7 in dense (5× 1018 m-3) plasmas for a nanotube radius of 25 nm, and tends to 1 at plasma densities below 1× 1017 m-3. The results obtained suggest that the local density of carbon adatoms on the nanotube side surface, at areas facing the adjacent nanotubes of the pattern, can be high enough to lead to the additional wall formation and thus cause the single- to multiwall structural transition, and other as yet unexplained nanoscience phenomena.

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The results of a hybrid numerical simulation of the growth kinetics of carbon nanowall-like nanostructures in the plasma and neutral gas synthesis processes are presented. The low-temperature plasma-based process was found to have a significant advantage over the purely neutral flux deposition in providing the uniform size distribution of the nanostructures. It is shown that the nanowall width uniformity is the best (square deviations not exceeding 1.05) in high-density plasmas of 3.0× 1018 m-3, worsens in lower-density plasmas (up to 1.5 in 1.0× 1017 m-3 plasmas), and is the worst (up to 1.9) in the neutral gas-based process. This effect has been attributed to the focusing of ion fluxes by irregular electric field in the vicinity of plasma-grown nanostructures on substrate biased with -20 V potential, and differences in the two-dimensional adatom diffusion fluxes in the plasma and neutral gas-based processes. The results of our numerical simulations are consistent with the available experimental reports on the effect of the plasma process parameters on the sizes and shapes of relevant nanostructures.

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Uniformity of postprocessing of large-area, dense nanostructure arrays is currently one of the greatest challenges in nanoscience and nanofabrication. One of the major issues is to achieve a high level of control in specie fluxes to specific surface areas of the nanostructures. As suggested by the numerical experiments in this work, this goal can be achieved by manipulating microscopic ion fluxes by varying the plasma sheath and nanorod array parameters. The dynamics of ion-assisted deposition of functional monolayer coatings onto two-dimensional carbon nanorod arrays in a hydrogen plasma is simulated by using a multiscale hybrid numerical simulation. The numerical results show evidence of a strong correlation between the aspect ratios and nanopattern positioning of the nanorods, plasma sheath width, and densities and distributions of microscopic ion fluxes. When the spacing between the nanorods and/or their aspect ratios are larger, and/or the plasma sheath is wider, the density of microscopic ion current flowing to each of the individual nanorods increases, thus reducing the time required to apply a functional monolayer coating down to 11 s for a 7-μm-wide sheath, and to 5 s for a 50-μm-wide sheath. The computed monolayer coating development time is consistent with previous experimental reports on plasma-assisted functionalization of related carbon nanostructures [B. N. Khare et al., Appl. Phys. Lett. 81, 5237 (2002)]. The results are generic in that they can be applied to a broader range of plasma-based processes and nanostructures, and contribute to the development of deterministic strategies of postprocessing and functionalization of various nanoarrays for nanoelectronic, biomedical, and other emerging applications.

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The results of numerical simulation of plasma-based, porous, template-assisted nanofabrication of Au nanodot arrays on highly-doped silicon taking into account typical electron density of low-temperature plasma of 1017-1018 m-3 and electron temperature of 2-5 eV are reported here. Three-dimensional microscopic topography of ion flux distribution over the outer and inner surfaces of the nanoporous template is obtained via numerical simulation of Au ion trajectories in the plasma sheath, in the close proximity of, and inside the nanopores. It is shown that, by manipulating the electron temperature, the cross-sheath potential drop, and by additionally altering the structure of the nanoporous template, one can control the ion fluxes within the nanopores, and eventually maximize the ion deposition onto the top surface of the developing crystalline Au nanodots (see top panel in the figure). In the same time, this procedure allows one to minimize amorphous deposits on the sidewalls that clutter and may eventually close the nanopores, thus disrupting the nanodot growth process, as it is shown in the bottom panel in the figure on the right.

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Unique features and benefits of the plasma-aided nanofabrication are considered by using the "plasma-building block" approach, which is based on plasma diagnostics and nanofilm characterization, cross-referenced by numerical simulation of generation and dynamics of building blocks in the gas phase, their interaction with nanostructured surfaces, and ab initio simulation of chemical structure of relevant nanoassemblies. The examples include carbon nanotip microemitter structures, semiconductor quantum dots and nanowires synthesized in the integrated plasma-aided nanofabrication facility.

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This contribution is focused on plasma-enhanced chemical vapor deposition systems and their unique features that make them particularly attractive for nanofabrication of flat panel display microemitter arrays based on ordered patterns of single-crystalline carbon nanotip structures. The fundamentals of the plasma-based nanofabrication of carbon nanotips and some other important nanofilms and nanostructures are examined. Specific features, challenges, and potential benefits of using the plasma-based systems for relevant nanofabrication processes are analyzed within the framework of the "plasma-building unit" approach that builds up on extensive experimental data on plasma diagnostics and nanofilm/nanostructure characterization, and numerical simulation of the species composition in the ionized gas phase (multicomponent fluid models), ion dynamics and interaction with ordered carbon nanotip patterns, and ab initio computations of chemical structure of single crystalline carbon nanotips. This generic approach is also applicable for nanoscale assembly of various carbon nanostructures, semiconductor quantum dot structures, and nano-crystalline bioceramics. Special attention is paid to most efficient control strategies of the main plasma-generated building units both in the ionized gas phase and on nanostructured deposition surfaces. The issues of tailoring the reactive plasma environments and development of versatile plasma nanofabrication facilities are also discussed.

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This paper offers numerical modelling of a waste heat recovery system. A thin layer of metal foam is attached to a cold plate to absorb heat from hot gases leaving the system. The heat transferred from the exhaust gas is then transferred to a cold liquid flowing in a secondary loop. Two different foam PPI (Pores Per Inch) values are examined over a range of fluid velocities. Numerical results are then compared to both experimental data and theoretical results available in the literature. Challenges in getting the simulation results to match those of the experiments are addressed and discussed in detail. In particular, interface boundary conditions specified between a porous layer and a fluid layer are investigated. While physically one expects much lower fluid velocity in the pores compared to that of free flow, capturing this sharp gradient at the interface can add to the difficulties of numerical simulation. The existing models in the literature are modified by considering the pressure gradient inside and outside the foam. Comparisons against the numerical modelling are presented. Finally, based on experimentally-validated numerical results, thermo-hydraulic performance of foam heat exchangers as waste heat recovery units is discussed with the main goal of reducing the excess pressure drop and maximising the amount of heat that can be recovered from the hot gas stream.

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The melting temperature of a nanoscaled particle is known to decrease as the curvature of the solid-melt interface increases. This relationship is most often modelled by a Gibbs--Thomson law, with the decrease in melting temperature proposed to be a product of the curvature of the solid-melt interface and the surface tension. Such a law must break down for sufficiently small particles, since the curvature becomes singular in the limit that the particle radius vanishes. Furthermore, the use of this law as a boundary condition for a Stefan-type continuum model is problematic because it leads to a physically unrealistic form of mathematical blow-up at a finite particle radius. By numerical simulation, we show that the inclusion of nonequilibrium interface kinetics in the Gibbs--Thomson law regularises the continuum model, so that the mathematical blow up is suppressed. As a result, the solution continues until complete melting, and the corresponding melting temperature remains finite for all time. The results of the adjusted model are consistent with experimental findings of abrupt melting of nanoscaled particles. This small-particle regime appears to be closely related to the problem of melting a superheated particle.

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Red blood cells (RBCs) are the most common type of cells in human blood and they exhibit different types of motions and deformed shapes in capillary flows. The behaviour of the RBCs should be studied in order to explain the RBC motion and deformation mechanism. This article presents a numerical simulation method for RBC deformation in microvessels. A two dimensional spring network model is used to represent the RBC membrane, where the elastic stretch/compression energy and the bending energy are considered with the constraint of constant RBC surface area. The forces acting on the RBC membrane are obtained from the principle of virtual work. The whole fluid domain is discretized into a finite number of particles using smoothed particle hydrodynamics concepts and the motions of all the particles are solved using Navier--Stokes equations. Minimum energy concepts are used to simulate the deformed shape of the RBC model. To verify the model, the motion of a single RBC is simulated in a Poiseuille flow and the characteristic parachute shape of the RBC is observed. Further simulations reveal that the RBC shows a tank treading motion when it flows in a linear shear flow.

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Iterative computational models have been used to investigate the regulation of bone fracture healing by local mechanical conditions. Although their predictions replicate some mechanical responses and histological features, they do not typically reproduce the predominantly radial hard callus growth pattern observed in larger mammals. We hypothesised that this discrepancy results from an artefact of the models’ initial geometry. Using axisymmetric finite element models, we demonstrated that pre-defining a field of soft tissue in which callus may develop introduces high deviatoric strains in the periosteal region adjacent to the fracture. These bone-inhibiting strains are not present when the initial soft tissue is confined to a thin periosteal layer. As observed in previous healing models, tissue differentiation algorithms regulated by deviatoric strain predicted hard callus forming remotely and growing towards the fracture. While dilatational strain regulation allowed early bone formation closer to the fracture, hard callus still formed initially over a broad area, rather than expanding over time. Modelling callus growth from a thin periosteal layer successfully predicted the initiation of hard callus growth close to the fracture site. However, these models were still susceptible to elevated deviatoric strains in the soft tissues at the edge of the hard callus. Our study highlights the importance of the initial soft tissue geometry used for finite element models of fracture healing. If this cannot be defined accurately, alternative mechanisms for the prediction of early callus development should be investigated.

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This paper aims to develop a meshless approach based on the Point Interpolation Method (PIM) for numerical simulation of a space fractional diffusion equation. Two fully-discrete schemes for the one-dimensional space fractional diffusion equation are obtained by using the PIM and the strong-forms of the space diffusion equation. Numerical examples with different nodal distributions are studied to validate and investigate the accuracy and efficiency of the newly developed meshless approach.

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This paper presents a feasibility study on structural damage alarming and localization of long-span cable-supported bridges using multi-novelty indices formulated by monitoring-derived modal parameters. The proposed method which requires neither structural model nor damage model is applicable to structures of arbitrary complexity. With the intention to enhance the tolerance to measurement noise/uncertainty and the sensitivity to structural damage, an improved novelty index is formulated in terms of auto-associative neural networks (ANNs) where the output vector is designated to differ from the input vector while the training of the ANNs needs only the measured modal properties of the intact structure under in-service conditions. After validating the enhanced capability of the improved novelty index for structural damage alarming over the commonly configured novelty index, the performance of the improved novelty index for damage occurrence detection of large-scale bridges is examined through numerical simulation studies of the suspension Tsing Ma Bridge (TMB) and the cable-stayed Ting Kau Bridge (TKB) incurred with different types of structural damage. Then the improved novelty index is extended to formulate multi-novelty indices in terms of the measured modal frequencies and incomplete modeshape components for damage region identification. The capability of the formulated multi-novelty indices for damage region identification is also examined through numerical simulations of the TMB and TKB.