665 resultados para Multiscale fractals
Resumo:
In this paper, cooperative self-assembly (CSA) of colloidal spheres with different sizes was studied. It was found that a complicated jamming effect makes it difficult to achieve an optimal self-assembling condition for construction of a well-ordered stacking of colloidal spheres in a relatively short growth time by CSA. Through the use of a characteristic infrared (IR) technique to significantly accelerate local evaporation on the growing interface without changing the bulk growing environment, a concise three-parameter (temperature, pressure, and IR intensity) CSA method to effectively overcome the jamming effect has been developed. Mono- and multiscale inverse opals in a large range of lattice scales can be prepared within a growth time (15-30 min) that is remarkably shorter than the growth times of several hours for previous methods. Scanning electron microscopy images and transmittance spectra demonstrated the superior crystalline and optical qualities of the resulting materials. More importantly, the new method enables optimal conditions for CSA without limitations on sizes and materials of multiple colloids. This strategy not only makes a meaningful advance in the applicability and universality of colloidal crystals and ordered porous materials but also can be an inspiration to the self-assembly systems widely used in many other fields, such as nanotechnology and molecular bioengineering.
Resumo:
The high Reynolds number flow contains a wide range of length and time scales, and the flow
domain can be divided into several sub-domains with different characteristic scales. In some
sub-domains, the viscosity dissipation scale can only be considered in a certain direction; in some
sub-domains, the viscosity dissipation scales need to be considered in all directions; in some
sub-domains, the viscosity dissipation scales are unnecessary to be considered at all.
For laminar boundary layer region, the characteristic length scales in the streamwise and normal
directions are L and L Re-1/ 2 , respectively. The characteristic length scale and the velocity scale in
the outer region of the boundary layer are L and U, respectively. In the neighborhood region of
the separated point, the length scale l<
Resumo:
A main method of predicting turbulent flows is to solve LES equations, which was called traditional LES method. The traditional LES method solves the motions of large eddies of size larger than filtering scale An while modeling unresolved scales less than Delta_n. Hughes et al argued that many shortcomings of the traditional LES approaches were associated with their inabilities to successfully differentiate between large and small scales. One may guess that a priori scale-separation would be better, because it can predict scale-interaction well compared with posteriori scale-separation. To this end, a multi-scale method was suggested to perform scale-separation computation. The primary contents of the multiscale method are l) A space average is used to differentiate scale. 2) The basic equations include the large scale equations and fluctuation equations. 3) The large-scale equations and fluctuation equations are coupled through turbulent stress terms. We use the multiscale equations of n=2, i.e., the large and small scale (LSS) equations, to simulate 3-D evolutions of a channel flow and a planar mixing layer flow Some interesting results are given.
Resumo:
Partial differential equations (PDEs) with multiscale coefficients are very difficult to solve due to the wide range of scales in the solutions. In the thesis, we propose some efficient numerical methods for both deterministic and stochastic PDEs based on the model reduction technique.
For the deterministic PDEs, the main purpose of our method is to derive an effective equation for the multiscale problem. An essential ingredient is to decompose the harmonic coordinate into a smooth part and a highly oscillatory part of which the magnitude is small. Such a decomposition plays a key role in our construction of the effective equation. We show that the solution to the effective equation is smooth, and could be resolved on a regular coarse mesh grid. Furthermore, we provide error analysis and show that the solution to the effective equation plus a correction term is close to the original multiscale solution.
For the stochastic PDEs, we propose the model reduction based data-driven stochastic method and multilevel Monte Carlo method. In the multiquery, setting and on the assumption that the ratio of the smallest scale and largest scale is not too small, we propose the multiscale data-driven stochastic method. We construct a data-driven stochastic basis and solve the coupled deterministic PDEs to obtain the solutions. For the tougher problems, we propose the multiscale multilevel Monte Carlo method. We apply the multilevel scheme to the effective equations and assemble the stiffness matrices efficiently on each coarse mesh grid. In both methods, the $\KL$ expansion plays an important role in extracting the main parts of some stochastic quantities.
For both the deterministic and stochastic PDEs, numerical results are presented to demonstrate the accuracy and robustness of the methods. We also show the computational time cost reduction in the numerical examples.