The Experts below are selected from a list of 243852 Experts worldwide ranked by ideXlab platform
Timon Rabczuk - One of the best experts on this subject based on the ideXlab platform.
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dual Support smoothed particle hydrodynamics for elastic mechanics
International Journal of Computational Methods, 2017Co-Authors: Zili Dai, Xiaoying Zhuang, Huilong Ren, Timon RabczukAbstract:In the standard smoothed particle hydrodynamics (SPH) method, the interaction between two particles might be not pairwise when the Support Domain varies, which can result in a reduction of accuracy. To deal with this problem, a modified SPH approach is presented in this paper. First of all, a Lagrangian kernel is introduced to eliminate spurious distortions of the Domain of material stability, and the gradient is corrected by a linear transformation so that linear completeness is satisfied. Then, concepts of Support and dual-Support are defined to deal with the unbalanced interactions between the particles with different Support Domains. Several benchmark problems in one, two and three dimensions are tested to verify the accuracy of the modified SPH model and highlight its advantages over the standard SPH method through comparisons.
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dual Support smoothed particle hydrodynamics for elastic mechanics
arXiv: Computational Physics, 2017Co-Authors: Zili Dai, Xiaoying Zhuang, Huilong Ren, Timon RabczukAbstract:In the standard SPH method, the interaction between two particles might be not pairwise when the Support Domain varies, which can result in a reduction of accuracy. To deal with this problem, a modified SPH approach is presented in this paper. First of all, a Lagrangian kernel is introduced to eliminate spurious distortions of the Domain of material stability, and the gradient is corrected by a linear transformation so that linear completeness is satisfied. Then, concepts of Support and dual-Support are defined to deal with the unbalanced interactions between the particles with different Support Domains. Several benchmark problems in one, two and three dimensions are tested to verify the accuracy of the modified SPH model and highlight its advantages over the standard SPH method through comparisons.
G R Liu - One of the best experts on this subject based on the ideXlab platform.
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a nodal integration technique for meshfree radial point interpolation method ni rpim
International Journal of Solids and Structures, 2007Co-Authors: G R Liu, Guiyong Zhang, Y Y Wang, Z H Zhong, Xu HanAbstract:A novel nodal integration technique for the meshfree radial point interpolation method (NI-RPIM) is presented for solid mechanics problems. In the NI-RPIM, radial basis functions (RBFs) augmented with polynomials are used to construct shape functions that possess the Delta function property. Galerkin weak form is adopted for creating discretized system equations, in which nodal integration is used to compute system matrices. A stable and simple nodal integration scheme is proposed to perform the nodal integration numerically. The NI-RPIM is examined using a number of example problems including stress analysis of an automobile mechanical component. The effect of shape parameters and dimension of local Support Domain on the results of the NI-RPIM is investigated in detail through these examples. The numerical solutions show that the present method is a robust, reliable, stable meshfree method and possesses better computational properties compared with traditional linear FEM and original RPIM using Gauss integration scheme.
Xiaoying Zhuang - One of the best experts on this subject based on the ideXlab platform.
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dual Support smoothed particle hydrodynamics for elastic mechanics
International Journal of Computational Methods, 2017Co-Authors: Zili Dai, Xiaoying Zhuang, Huilong Ren, Timon RabczukAbstract:In the standard smoothed particle hydrodynamics (SPH) method, the interaction between two particles might be not pairwise when the Support Domain varies, which can result in a reduction of accuracy. To deal with this problem, a modified SPH approach is presented in this paper. First of all, a Lagrangian kernel is introduced to eliminate spurious distortions of the Domain of material stability, and the gradient is corrected by a linear transformation so that linear completeness is satisfied. Then, concepts of Support and dual-Support are defined to deal with the unbalanced interactions between the particles with different Support Domains. Several benchmark problems in one, two and three dimensions are tested to verify the accuracy of the modified SPH model and highlight its advantages over the standard SPH method through comparisons.
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dual Support smoothed particle hydrodynamics for elastic mechanics
arXiv: Computational Physics, 2017Co-Authors: Zili Dai, Xiaoying Zhuang, Huilong Ren, Timon RabczukAbstract:In the standard SPH method, the interaction between two particles might be not pairwise when the Support Domain varies, which can result in a reduction of accuracy. To deal with this problem, a modified SPH approach is presented in this paper. First of all, a Lagrangian kernel is introduced to eliminate spurious distortions of the Domain of material stability, and the gradient is corrected by a linear transformation so that linear completeness is satisfied. Then, concepts of Support and dual-Support are defined to deal with the unbalanced interactions between the particles with different Support Domains. Several benchmark problems in one, two and three dimensions are tested to verify the accuracy of the modified SPH model and highlight its advantages over the standard SPH method through comparisons.
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A Meshless Local Petrov-Galerkin Shepard and Least-Squares Method Based on Duo Nodal Supports
Hindawi Limited, 2014Co-Authors: Xiaoying Zhuang, Yongchang CaiAbstract:The meshless Shepard and least-squares (MSLS) interpolation is a newly developed partition of unity- (PU-) based method which removes the difficulties with many other meshless methods such as the lack of the Kronecker delta property. The MSLS interpolation is efficient to compute and retain compatibility for any basis function used. In this paper, we extend the MSLS interpolation to the local Petrov-Galerkin weak form and adopt the duo nodal Support Domain. In the new formulation, there is no need for employing singular weight functions as is required in the original MSLS and also no need for background mesh for integration. Numerical examples demonstrate the effectiveness and robustness of the present method
Vinod A Kumar - One of the best experts on this subject based on the ideXlab platform.
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coupled groundwater flow and contaminant transport simulation in a confined aquifer using meshfree radial point collocation method rpcm
Engineering Analysis With Boundary Elements, 2016Co-Authors: Guneshwor L Singh, T I Eldho, Vinod A KumarAbstract:Abstract In this study, a meshfree radial point collocation method is used to model the contaminant transport through confined aquifer. The discretization of the governing equations is done by a point collocation method and radial basis functions (RBF) are used as the interpolation function. For comparative study, two widely used radial basis functions namely multi-quadrics and exponential RBF are used. A local circular Support Domain is employed to construct the shape functions. In the model, no information on nodal inter-relationship is required for shape function construction except the nodal coordinates, unlike in finite-difference (FDM) or finite-element (FEM) based methods. The developed model is validated through benchmark problems in one and two dimensions. Further, application of the model for advective transport with high Peclet number has been studied and the model has been found to be effective in handling the instability of high Peclet problems. For the field problem considered, the results obtained from the model have been compared with the FEM solution and was found to be satisfactory. This method is relatively easy to implement and offers better accuracy with acceptable computational time. Considering the significant advantages offered by this method, it can serve as a good alternative to the conventional methods.
Hilary Coo - One of the best experts on this subject based on the ideXlab platform.
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lineage visualizing multivariate clinical data in genealogy graphs
IEEE Transactions on Visualization and Computer Graphics, 2019Co-Authors: Carolina Nobre, Nils Gehlenborg, Hilary CooAbstract:The majority of diseases that are a significant challenge for public and individual heath are caused by a combination of hereditary and environmental factors. In this paper we introduce Lineage, a novel visual analysis tool designed to Support Domain experts who study such multifactorial diseases in the context of genealogies. Incorporating familial relationships between cases with other data can provide insights into shared genomic variants and shared environmental exposures that may be implicated in such diseases. We introduce a data and task abstraction, and argue that the problem of analyzing such diseases based on genealogical, clinical, and genetic data can be mapped to a multivariate graph visualization problem. The main contribution of our design study is a novel visual representation for tree-like, multivariate graphs, which we apply to genealogies and clinical data about the individuals in these families. We introduce data-driven aggregation methods to scale to multiple families. By designing the genealogy graph layout to align with a tabular view, we are able to incorporate extensive, multivariate attributes in the analysis of the genealogy without cluttering the graph. We validate our designs by conducting case studies with our Domain collaborators.
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lineage visualizing multivariate clinical data in genealogy graphs
bioRxiv, 2017Co-Authors: Carolina Nobre, Nils Gehlenborg, Hilary CooAbstract:The majority of diseases that are a significant challenge for public and individual heath are caused by a combination of hereditary and environmental factors. In this paper, we introduce Lineage, a novel visual analysis tool, designed to Support Domain experts that study such multifactorial diseases in the context of genealogies. Incorporating familial relationships between cases can provide insights into shared genomic variants that could be implicated in diseases, but also into shared environmental exposures. We introduce a data and task abstraction and argue that the problem of analyzing such diseases based on genealogical, clinical, and genetic data can be mapped to a multivariate graph visualization problem. Our main contribution is a novel visual representation for tree-like, multivariate graphs, which we apply to genealogies and clinical data about the individuals in these families. We introduce data-driven aggregation methods to scale to multiple families with hundreds of members across several generations. By designing the genealogy graph layout to align with a tabular view that displays clinical data for each family member, we are able to incorporate extensive, multivariate attributes in the analysis of the genealogy without cluttering the graph. We also discuss how the principles of our methodology can be generalized to other scenarios. We validate our designs using an illustrative example based on real-world data, and report of feedback from Domain experts.
