Elsevier

Computers & Structures

Volume 87, Issues 3–4, February 2009, Pages 141-150
Computers & Structures

A three-dimensional nodal-based implementation of a family of discontinuous Galerkin methods for elasticity problems

https://doi.org/10.1016/j.compstruc.2008.11.009Get rights and content

Abstract

Four discontinuous Galerkin (DG) methods are proposed to enrich the resource of modeling elasticity problems as they are volume locking-free and allow hanging nodes in meshing. A detailed finite element formulation of these DG methods is presented. For implementation, we coded a three-dimensional nodal-based DG program in which the conventional nodal-based pure displacement finite element codes are fully exploited. The robustness and accuracy of each DG method are demonstrated and compared with mixed methods through solving a rubber beam problem. The coupled use of DG with continuous elements is proposed for some practical applications.

Introduction

In general, the popular pure displacement-based continuous Galerkin (CG) methods work well for linear elasticity problems with normal materials. However, their performance can be detrimental for cases where materials are highly incompressible [5]. In these cases, CG provides a smaller displacement solution, called volume locking. Methods for handling the volume locking include mixed finite element methods, reduced integrations, nonconforming methods, and stabilized finite elements [3], [6], [12], [14], [21], [22]. The locking may be completely removed using mixed finite element methods. However, the selection of the spaces for displacement and pressure is not independent and they must satisfy the BB condition [2]. Consequently, only 27-nodal elements with linear pressure variations (Q2/P1) and 27-nodal Taylor–Hood elements with continuous pressures (Q2/Q1) are the lowest order 3D elements that strictly satisfy the BB condition and exhibit optimal convergent rates [5]. The reduced integration method greatly reduces the accuracy. The lack of the coercivity in lower order nonconforming elements results in divergent solutions. Intensive trials for searching for an appropriate stabilized parameter required for stabilized finite element methods are impractical. We propose a family of DG methods for some practical applications to handle the locking for highly incompressible elasticity.

The main disadvantage for DG methods is the great increase in unknowns. Considering their many advantages over CG methods, however, DG methods can still be proposed for some practical applications. First, the feature of momentum conservation satisfied locally and weakly is very important to achieve a satisfactory stress result for elasticity problems with nearly incompressible materials. Second, DG allows hanging nodes that greatly facilitate the adaptive refinement on an original mesh in that each element can be refined or coarsened arbitrarily and independently, which could be a challenge for CG methods. Third, it has a potential to facilitate parallel computing. Fourth, it is a natural method to model some localization problems where the displacement field is discontinuous. Finally, the explosion in unknowns of DG methods can be alleviated by a coupled use of DG with CG methods in some cases, as explained in the section of numerical study.

The idea of DG finite element methods originated from Nitsche’s work in 1971 [15]. Rather than enforcing the Dirichlet boundary condition strongly in CG methods, he did it weakly. In 1976, the continuity of the stress in elliptic equations and the flux in parabolic equations across the interior faces between elements was weakly enforced by Douglas and Dupont [11]. The Interior Penalty Galerkin (IPG or SIPG) finite element method was first derived and formulated for second order elliptic equations by Wheeler [24] and Wheeler and Percell [19]. In their DG formulations, the stiffness contributed from interior faces is obtained by using the average of tractions and jumps on primary variables across the faces between elements. Also, the interior continuity condition of the primary variable is controlled by using a penalty method to add a penalty term involving the jump on the primary variable and its corresponding test function. By adjusting the penalty parameter, an accurate result may be obtained. If the penalty parameter is set to infinity, DG coincides with CG. The IPG method was exploited by Arnold [1] to solve parabolic equations and nonlinear elliptic problems. In addition, the penalty methods should be understood here. In CG framework, similar penalty techniques have been used to enforce the non-penetration condition for contact mechanics problems [16] and the rotation continuity condition for beam problems [4]. For example, in a popular and efficient pipe elbow element originally formulated by Bathe and Almelda [4], the jump of the first derivative of the continuous ovalization displacement on the interior jointed element face is penalized through incorporating a penalty energy function into the potential, in which the accuracy of the slope continuity across the joints is able to be improved by adjusting the penalty parameter.

Since finite element methods were developed, much research work has been focused on CG methods. Recently, DG methods have become more popular and have been exploited to deal with the challenges that CG methods are not able to handle easily [9]. A non-symmetric DG method proposed by Oden, Babuska and Baumann (OBB) [17] to solve diffusion problems results in a positive definite stiffness matrix. Therefore, the method is more stable and robust than the symmetric DG formulation, and it exhibits a property of local mass conservation at the element level, which is very important for solving convection and/or diffusion problems. In addition, Cockburn and Shu [8] developed the local DG (LDG), another family of DG which is different from the primal DG. This LDG was extended by Cockburn and Dawson [7] for convection–diffusion equations in multi-dimensions. In the LDG method, besides the primary variable, the flux also appears as an unknown.

Because of the symmetric advantage of the stiffness matrix, SIPG is often applied to problems that do not have strict stability requirements. SIPG was also used by Hansbo and Larson [13] to solve 2-D nearly incompressible elasticity and Stokes flow problems. Based on both IPG and OBB, a Non-Symmetric Interior Penalty Galerkin (NIPG) formulation was presented by Wheeler et al. [20] to solve elasticity problems. This formulation exhibits more stable and robust behavior than SIPG. Compared to OBB, NIPG allows one to adjust penalty parameters to achieve more accurate results. A new scheme, the Incomplete Interior Penalty Galerkin (IIPG) method proposed by Dawson et al. [10], has the best performance in terms of stability and accuracy of solutions for solving fluid problems. However, IIPG has not been studied for elasticity problems.

Recent effort in modeling elasticity problems by using DG methods [20], [13], [26] focused mostly on theoretical work on the convergence, stability, and locking free property of DG methods and on 2D implementations. The lack of effort in comparing the performance of different DG methods for 3D problems is obvious in the literature. In this paper, we compare the robustness and accuracy of four DG methods with the mixed method applied to 3D elasticity problems with highly incompressible materials. This work is important for selections on DG methods for practical engineering applications. Another important factor affecting DG application to practical problems is their implementations currently dominated by non-nodal based programs. Although these implementations are easy for full DG discretizations, it is difficult to use the coupling between continuous and discontinuous elements. In fact, the popular commercial finite element codes are nodal-based programs for CG methods. For our proposed four DG methods, we present a general 3D nodal-based implementation that is able to fully exploit a conventional 3D elasticity code and naturally handle the coupling of continuous and discontinuous elements. Adding interface stiffness into a CG code, which is actually computed using the same shape functions as CG programs, is only the additional work for this DG implementation. In Section 2, we formulate a family of DG methods for elasticity problems. In Section 3, we describe a 3D nodal-based implementation of DG methods and describe the procedures to construct interface stiffness. In Section 4, we compare the robustness and accuracy of our four DG methods with a mixed method using a nearly incompressible beam problem. The coupled use of DG with CG methods is also proposed in this section. Conclusions are provided in the final section.

Section snippets

DG formulation on elasticity problem

Let a body occupy a domain ΩR3 shown in Fig. 1. Ω has a boundary surface Ω which is further divided into Γu and Γt withΩ=Γ¯uΓ¯t,ΓuΓt=,where the prescribed displacement u¯(x)H1(Γu) is given on the part Γu of the boundary and the surface traction t¯(x)L2(Γt) is given on the remainder Γt of the boundary. We denote the body force by f(x)L2(Ω), the Cauchy stress tensor by σ and the displacement field by variable u. The linear momentum equation for three-dimensional linear elasticity is·σ+f=

A nodal-based DG implementation

The popular CG finite element codes are nodal-based. In general, a CG program uses geometry data containing the coordinates of nodes. The profile of an element is defined by its nodes. These nodes completely determine the order of the element. Moreover, as the solutions are just the values at nodes, they can be directly used for output and visualization without any further post-processing. The nodal-based CG computer programs for linear elasticity have been thoroughly implemented, tested, and

Numerical study

We consider a three-dimensional version of a cantilever beam problem with similar data used in [5]. This beam is shown in Fig. 5 but drawn only in yz plane. The displacement boundary conditions are represented by the rollers. The constrains in the x-direction are on only the surfaces at z=±20mm. The beam with 1 mm width is loaded by a uniform pressure on its top surface. We studied two cases, Poisson’s ratio ν=0.3 and ν=0.499. In the following subsections, the more accurate results are

Conclusions

We have presented a formulation and implementation of a family of DG methods for solving elasticity problems. The key procedure for DG methods is to add the interface stiffness into a nodal-based CG program. The normal matrix for stiffness computation of a general curved interface has been introduced in this paper, which leads to a practical compacted Voigt implementation. Our numerical study demonstrates: (a) All proposed DG methods greatly improve the stress prediction when compared to CG

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