919 resultados para progressive mesh


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Flow around moving boundary is ubiquitous in engineering applications. To increse the efficienly of the algorithm to handle moving boundaries is still a major challenge in Computational Fluid Dynamics (CFD). The Chimera grid method is one type of method to handle moving boundaries. A concept of domain de-composition has been proposed in this paper. In this method, sub-domains are meshed independently and governing equations are also solved separately on them. The Chimera grid method was originally used only on structured (curvilinear) meshes. However, in a problem which involves both moving boundary and complex geometry, the number of sub-domains required in a traditional (structured) Chimera method becomes fairly large. Thus the time required in the interior boundary locating, link-building and data exchanging also increases. The use of unstructured Chimera grid can reduce the time consumption significantly by the reduction of domain(block) number. Generally speaking, unstructured Chimera grid method has not been developed. In this paper, a well-known pressure correction scheme - SIMPLEC is modified and implemented on unstructured Chimera mesh. A new interpolation scheme regarding the pressure correction is proposed to prevent the possible decoupling of pressure. A moving-mesh finite volume approach is implemented in an inertial reference frame. This approach is then used to compute incompressible flow around a rotating circular and elliptic cylinder. These numerical examples demonstrate the capability of the proposed scheme in handling moving boundaries. The numerical results are in good agreement with other experimental and computational data in literature. The method proposed in this paper can be efficiently applied to more challenge cases such as free-falling objects or heavy particles in fluid.

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The minimum length at first maturity of Clarias lazera was found to be 24 cm (4.8%) for females and 20 cm (1.8%) for males. Fifty percent maturity was attained at length of 28 cm to 30 cm for both sexes; there being little difference among the sexes at this level of maturity. The modal retention lengths for gill nets were: 13 cm for 25.5 mm mesh; 18 cm for 32 mm mesh; 28 cm for 57 mm mesh; and 38 cm for 76 mm mesh. Modal lengths of Clarias lazera caught by various hooks sizes were No. 10 (28 cm); No. 11 (33 cm); Nos. 15 and 16 (28 cm). It is recommended that to protect the clarias fishery in Lake Chad, the use of gill nets of less than 57 mm mesh size and fishing hook No. 16 (and smaller sizes) which caught 43.94% of immature fishes should be discouraged

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A numerical 2D method for simulation of two-phase flows including phase change under microgravity conditions is presented in this paper, with a level set method being coupled with the moving mesh method in the double-staggered grid systems. When the grid lines bend very much in a curvilinear grid, great errors may be generated by using the collocated grid or the staggered grid. So the double-staggered grid was adopted in this paper. The level set method is used to track the liquid-vapor interface. The numerical analysis is fulfilled by solving the Navier-Stokes equations using the SIMPLER method, and the surface tension force is modeled by a continuum surface force approximation. A comparison of the numerical results obtained with different numerical strategies shows that the double-staggered grid moving-mesh method presented in this paper is more accurate than that used previously in the collocated grid system. Based on the method presented in this paper, the condensation of a single bubble in the cold water under different level of gravity is simulated. The results show that the condensation process under the normal gravity condition is different from the condensation process under microgravity conditions. The whole condensation time is much longer under the normal gravity than under the microgravity conditions.

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Approximately two-thirds of coastal and Great Lakes states have some type of shoreline construction setback or construction control line requiring development to be a certain distance from the shoreline or other coastal feature (OCRM, 2008). Nineteen of 30 coastal states currently use erosion rates for new construction close to the shoreline. Seven states established setback distances based on expected years from the shoreline: the remainder specify a fixed setback distance (Heinz Report, 2000). Following public hearings by the County of Kauai Planning Commission and Kauai County Council, the ‘Shoreline Setback and Coastal Protection Ordinance’ was signed by the Mayor of Kauai on January 25, 2008. After a year of experience implementing this progressive, balanced shoreline setback ordinance several amendments were recently incorporated into the Ordinance (#887; Bill #2319 Draft 3). The Kauai Planning Department is presently drafting several more amendments to improve the effectiveness of the Ordinance. The intent of shoreline setbacks is to establish a buffer zone to protect shorefront development from loss due to coastal erosion - for a period of time; to provide protection from storm waves; to allow the natural dynamic cycles of erosion and accretion of beaches and dunes to occur; to maintain beach and dune habitat; and, to maintain lateral beach access and open space for the enjoyment of the natural shoreline environment. In addition, a primary goal of the Kauai setback ordinance is to avoid armoring or hardening of the shore which along eroding coasts has been documented to ultimately eliminate the fronting beach. (PDF contains 4 pages)

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Moving mesh methods (also called r-adaptive methods) are space-adaptive strategies used for the numerical simulation of time-dependent partial differential equations. These methods keep the total number of mesh points fixed during the simulation, but redistribute them over time to follow the areas where a higher mesh point density is required. There are a very limited number of moving mesh methods designed for solving field-theoretic partial differential equations, and the numerical analysis of the resulting schemes is challenging. In this thesis we present two ways to construct r-adaptive variational and multisymplectic integrators for (1+1)-dimensional Lagrangian field theories. The first method uses a variational discretization of the physical equations and the mesh equations are then coupled in a way typical of the existing r-adaptive schemes. The second method treats the mesh points as pseudo-particles and incorporates their dynamics directly into the variational principle. A user-specified adaptation strategy is then enforced through Lagrange multipliers as a constraint on the dynamics of both the physical field and the mesh points. We discuss the advantages and limitations of our methods. The proposed methods are readily applicable to (weakly) non-degenerate field theories---numerical results for the Sine-Gordon equation are presented.

In an attempt to extend our approach to degenerate field theories, in the last part of this thesis we construct higher-order variational integrators for a class of degenerate systems described by Lagrangians that are linear in velocities. We analyze the geometry underlying such systems and develop the appropriate theory for variational integration. Our main observation is that the evolution takes place on the primary constraint and the 'Hamiltonian' equations of motion can be formulated as an index 1 differential-algebraic system. We then proceed to construct variational Runge-Kutta methods and analyze their properties. The general properties of Runge-Kutta methods depend on the 'velocity' part of the Lagrangian. If the 'velocity' part is also linear in the position coordinate, then we show that non-partitioned variational Runge-Kutta methods are equivalent to integration of the corresponding first-order Euler-Lagrange equations, which have the form of a Poisson system with a constant structure matrix, and the classical properties of the Runge-Kutta method are retained. If the 'velocity' part is nonlinear in the position coordinate, we observe a reduction of the order of convergence, which is typical of numerical integration of DAEs. We also apply our methods to several models and present the results of our numerical experiments.