For finite element analysis of structures with irregular geometry, unsatisfactory meshing quality could be the major concern. Adaptive meshing technique is usually applied to modulate the mesh to approach the geometry...
详细信息
For finite element analysis of structures with irregular geometry, unsatisfactory meshing quality could be the major concern. Adaptive meshing technique is usually applied to modulate the mesh to approach the geometry. The stress solution from triangular elements is understood less accurate than that of quadrilateral elements. Therefore, adaptive technique for quadrilateral elements is desirable for more proficient analysis of complex geometry. This paper develops a novel adaptive technique that combines a newly developed quadtree algorithm with the cell-based smoothed finite element method (CS-FEM) for automatic mesh adaptation using quadrilateral elements. Since the quadtree algorithm generates a grid with different sizes of quadrilaterals, a number of new CS-FEM elements of n-sided polygon are concomitantly constituted. In the adaptation process, the energy error norm and the geometrical feature are applied as the calibrations for the adaptive refinement. The elements on curved boundaries are either cut or merged with the surrounding elements automatically. It is found that the present new quadtree algorithm works very effectively with the CS-FEM formulation in view of stability and convergence. The results by the current S-FEM are found generally more accurate than those of the general finite element method (FEM) counterpart, especially in terms of strain energy solutions.
This study develops a sequential multiscale model to investigate the interface failure of graphene-reinforced epoxy nanocomposites. The molecular dynamics simulations are carried out to track the graphene-epoxy interf...
详细信息
This study develops a sequential multiscale model to investigate the interface failure of graphene-reinforced epoxy nanocomposites. The molecular dynamics simulations are carried out to track the graphene-epoxy interface behavior through normal opening and tangential sliding modes modeling at nanoscale. Four kinds of functional groups on the graphene including -OH, -NH2, -CH3 and -COOH are considered. The traction-separation law in the normal direction and the shear-lag model in the tangential direction are used to mimic the interface behavior. Furthermore, the scaled boundary finite element method in collaboration with a new hybrid quadtree algorithm is used to discretize the nanocomposite representative volume element at microscale. In addition to the functional group types, the volume fraction and aspect ratio of the graphene nanoplatelets are taken into account in the microscale simulation. The results show that the addition of functional groups to graphene can greatly improve the load-bearing capacity of the interface between nanoplatelets and epoxy resin. Meanwhile, the reinforcement effect of nanoplatelets is related to their aspect ratio and volume fraction. The efficiency and accuracy of the proposed model are validated by comparing the results with traditional finite element method. This study provides a theoretical support and guidance for the design and fabrication of graphene reinforced nanocomposites.
With the development of the economy and society, porous materials have been widely used in various fields due to their unique structure and function. Therefore, it is of great significance to analyze the mechanical pr...
详细信息
With the development of the economy and society, porous materials have been widely used in various fields due to their unique structure and function. Therefore, it is of great significance to analyze the mechanical properties of porous materials. In traditional analysis methods, experimental and numerical simulation methods are mainly used. When conducting finite element numerical simulation analysis on porous materials, a large number of fine grids need to be divided, and the calculation process is time-consuming and laborious. This article randomly generates porous microstructure models through algorithms and uses efficient quadtree algorithms to calculate their mechanical properties, thereby obtaining a large amount of machine-learning sample data. Furthermore, a neural network-based machine learning algorithm is established to predict the mechanical properties of porous materials. By using microstructure images as the input layer of the model, the mechanical properties under corresponding conditions can be directly predicted. This study provides a new method for predicting mechanical properties based on microstructure images. It has been verified that the mechanical properties directly predicted by the network are similar to the actual ones, with high accuracy and computational efficiency.
The contribution at hand presents the implementation of a non-linear constitutive model for rate-dependent inelasticity into the scaled boundary finite element method (SBFEM). To increase the numerical efficiency and ...
详细信息
The contribution at hand presents the implementation of a non-linear constitutive model for rate-dependent inelasticity into the scaled boundary finite element method (SBFEM). To increase the numerical efficiency and simplify the formulation, the stress update algorithm is only performed at the scaling centre of the polytope elements. The presented SBFEM framework is ideally suited for the image-based analysis of composites since many matrix materials exhibit rate-dependent inelasticity, particularly at high temperatures. Thereby, meshes are generated based on images of the complex microstructures by employing an efficient quadtree-decomposition. The main advantage of this approach lies in its high degree of automation requiring only minimal intervention by the user. Various benchmark examples are presented to verify the formulation. Furthermore, the influence of jagged boundaries, resulting from the quadtree decomposition, on the accuracy and convergence of results is discussed in detail. The paper concludes with the study of a metal-matrix composite, whereby rate-dependent inelasticity is taken into account to model the mechanical behaviour of the matrix.
Low-light images often suffer from poor quality and low visibility. Improving the quality of low-light image is becoming a highly desired subject in both computational photography and computer vision applications. Thi...
详细信息
ISBN:
(纸本)9789811072994;9789811072987
Low-light images often suffer from poor quality and low visibility. Improving the quality of low-light image is becoming a highly desired subject in both computational photography and computer vision applications. This paper proposes an effective method to constrain the illumination map t by estimating the norm and constructing the constraint coefficients, which called LieCNE. More specifically, we estimate the initial illumination map by finding the maximum value of R, G and B channels and optimize it by norm estimation. We propose a function t. to contain the exponential power. in order to optimize the enhancement effect under different illumination conditions. Finally, a new evaluation criterion is also proposed. We use the similarity with the true value to determine the enhanced effect. Experimental results show that LieCNE exhibits better performance under a variety of lighting conditions in enhancement results and image spillover prevention.
The U.S. Army Research Laboratory (ARL) is investigating an efficient SAR image formation algorithm to support its mission-funded Ultra-Wideband (UWB) BoomSAR program. The traditional Backprojection technique produces...
详细信息
ISBN:
(纸本)0819436674
The U.S. Army Research Laboratory (ARL) is investigating an efficient SAR image formation algorithm to support its mission-funded Ultra-Wideband (UWB) BoomSAR program. The traditional Backprojection technique produces images, requires no memory resources and allows arbitrary motion;however it is very computationally intensive and is therefor appropriate only for postprocessing applications. ARL invented a new recursive backprojector that reduces the computational load from an order N-3 to N(2)Log(N) [1]. This new algorithm is competitive in speed with the frequency domain omega K processing but requires less memory, and produces fewer artifacts. We compares both algorithms and presents the results of using simulation data and real data.
暂无评论