2018
DOI: 10.1016/j.cma.2018.05.010
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A reproducing kernel enhanced approach for peridynamic solutions

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Cited by 47 publications
(26 citation statements)
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“…[15] showed the equivalence between the PD differential operator [24] and the RK implicit gradient operator [11], which both can be employed to obtain more accurate meshfree gradients, such as a deformation gradient of higher-order accuracy. Reproducing kernel enhanced approaches have been proposed to improve meshfree integration in peridynamic models [15,19,28].…”
Section: Introductionmentioning
confidence: 99%
“…[15] showed the equivalence between the PD differential operator [24] and the RK implicit gradient operator [11], which both can be employed to obtain more accurate meshfree gradients, such as a deformation gradient of higher-order accuracy. Reproducing kernel enhanced approaches have been proposed to improve meshfree integration in peridynamic models [15,19,28].…”
Section: Introductionmentioning
confidence: 99%
“…The effect of numerical integration in the non-local integrals has also been a focus in studies, as it may also have a strong effect on convergence in peridynamics [46][47][48][49][50]. In the first meshfree implementation of peridynamics [24], the peridynamic equation of motion was discretized by nodal integration with the full physical nodal volume as the integration weight, resulting in the so-called full volume (FV) integration.…”
Section: Introductionmentioning
confidence: 99%
“…These techniques exhibit firstorder convergence in displacements [46]. The limitation of first-order convergence was attributed in [50] to the piecewise constant nature of the approximation employed, where the reproducing kernel approximation was introduced in the peridynamic displacement field to increase the convergence rate. However, high-order Gauss integration was employed to achieve the integration accuracy necessary to avoid the aforementioned oscillatory convergence behavior, resulting in an increased computational cost.…”
Section: Introductionmentioning
confidence: 99%
“…In a narrow sense, SPH is a numerical solution, kernel approximation method, for differential terms. The differences between PD and SPH are listed as follows: From the mechanical perspectives, the applied disciplines are initially different in PD and SPH, namely solid mechanics and fluid mechanics. The force between two interaction material points is not always equal in state‐based PD, but is definitely equal in SPH. The material constitution law is included in the particle properties in SPH theory rather than is incorporated in the bond in PD theory. The formulation of the traditional PD employs a total Lagrangian formulation which is based on the material coordinate, while the formulation of the traditional SPH employs an updated Lagrangian formulation which is based on the spatial coordinate. In the same time, the PD theory has many similarities with SPH in physical background and numerical implementation as follows: The same physical model, nonlocal model, is employed in these two theories, which both consider the interaction of a finite influence domain. These two theories both employ a Newton's second law and present a dynamic mechanical method. The material property and tracking perspective are both a Lagrangian view which is fixed on material point in PD and SPH. The discretization equation of PD theory is similar to that of SPH when the meshless technology is used to solve PD theory 23–27 …”
Section: Nonlocal Backgroundmentioning
confidence: 99%