The smoothed finite element method (S-FEM) was originated by G R Liu by combining some meshfree techniques with the well-established standard finite element method (FEM). It has a family of models carefully designed with innovative types of smoothing domains. These models are found having a number of important and theoretically profound properties. This article first provides a concise and easy-to-follow presentation of key formulations used in the S-FEM. A number of important properties and unique features of S-FEM models are discussed in detail, including 1) theoretically proven softening effects; 2) upper-bound solutions; 3) accurate solutions and higher convergence rates; 4) insensitivity to mesh distortion; 5) Jacobian-free; 6) volumetric-locking-free; and most importantly 7) working well with triangular and tetrahedral meshes that can be automatically generated. The S-FEM is thus ideal for automation in computations and adaptive analyses, and hence has profound impact on AI-assisted modeling and simulation. Most importantly, one can now purposely design an S-FEM model to obtain solutions with special properties as wish, meaning that S-FEM offers a framework for design numerical models with desired properties. This novel concept of numerical model on-demand may drastically change the landscape of modeling and simulation. Future directions of research are also provided.
. [J]. Frontiers of Structural and Civil Engineering, 2019, 13(2): 456-477.
Gui-Rong Liu. The smoothed finite element method (S-FEM): A framework for the design of numerical models for desired solutions. Front. Struct. Civ. Eng., 2019, 13(2): 456-477.
SD’s or smoothing cells (SC’s) are divided from and located within the elements (,)
CS-FEM nCS-FEM
1D, 2D, 3D softer; high accuracy; insensitive to mesh distortion
Edge-based SD (ESD)
SD’s are created based on edges by connecting portions of the surrounding elements sharing the associated edge ()
ES-FEM
2D, 3D softer; very high accuracy, less insensitive to mesh distortion
Node-based SD (NSD)
SD’s are created based on nodes by connecting portions of the surrounding elements sharing the associated node ()
NS-FEM
1D, 2D, 3D soft; upper bound, very insensitive to mesh distortion, volumetric locking free
Face-based SD (FSD)
SD’s are created based on faces by connecting portions of the surrounding elements sharing the associated face ()
FS-FEM
3D softer; very high accuracy, less insensitive to mesh distortion
Tab.1
Fig.7
Fig.8
dimension of the problem
minimum number of smoothing domains
1D
= nt
2D
= 2nt /3
3D
= 3nt /6= nt /2
Tab.2
Fig.9
point
N1
N2
N3
N4
description
1
1.0
0
0
0
field node
2
0
1.0
0
0
field node
3
0
0
1.0
0
field node
4
0
0
0
1.0
field node
5
1/2
1/2
0
0
side midpoint
6
0
1/2
1/2
0
side midpoint
7
0
0
1/2
1/2
side midpoint
8
1/2
0
0
1/2
side midpoint
9
1/4
1/4
1/4
1/4
intersection of two bi-medians
g1
3/4
1/4
0
0
Gauss point (mid-segment point of )
g2
3/8
3/8
1/8
1/8
Gauss point (mid-segment point of )
g3
3/8
1/8
1/8
3/8
Gauss point (mid-segment point of )
g4
3/4
0
0
1/4
Gauss point (mid-segment point of )
g5
1/4
3/4
0
0
Gauss point (mid-segment point of )
g6
0
3/4
1/4
0
Gauss point (mid-segment point of )
g7
1/8
3/8
3/8
1/8
Gauss point (mid-segment point of )
g8
0
1/4
3/4
0
Gauss point (mid-segment point of )
g9
0
0
3/4
1/4
Gauss point (mid-segment point of )
g10
1/8
1/8
3/8
3/8
Gauss point (mid-segment point of )
g11
0
0
1/4
3/4
Gauss point (mid-segment point of )
g12
1/4
0
0
3/4
Gauss point (mid-segment point of )
Tab.3
point
N1’
N2’
N3’
N4’
N5’
N6’
description
1’
1.0
0
0
0
0
0
field node
2’
0
1.0
0
0
0
0
field node
3’
0
0
1.0
0
0
0
field node
4’
0
0
0
1.0
0
0
field node
5’
0
0
0
0
1.0
0
field node
6’
0
0
0
0
0
1.0
field node
O
1/6
1/6
1/6
1/6
1/6
1/6
centroid point
g1’
7/12
1/12
1/12
1/12
1/12
1/12
Gauss point (mid-segment point of )
g2’
1/2
1/2
0
0
0
0
Gauss point (mid-segment point of )
g3’
1/12
7/12
1/12
1/12
1/12
1/12
Gauss point (mid-segment point of )
g4’
0
1/2
1/2
0
0
0
Gauss point (mid-segment point of )
g5’
1/12
1/12
7/12
1/12
1/12
1/12
Gauss point (mid-segment point of )
g6’
0
0
1/2
1/2
0
0
Gauss point (mid-segment point of )
g7’
1/12
1/12
1/12
7/12
1/12
1/12
Gauss point (mid-segment point of )
g8’
0
0
0
1/2
1/2
0
Gauss point (mid-segment point of )
g9’
1/12
1/12
1/12
1/12
7/12
1/12
Gauss point (mid-segment point of )
g10’
0
0
0
0
1/2
1/2
Gauss point (mid-segment point of )
g11’
1/12
1/12
1/12
1/12
1/12
7/12
Gauss point (mid-segment point of )
g12’
1/2
0
0
0
0
1/2
Gauss point (mid-segment point of )
Tab.4
Fig.10
Fig.11
Fig.12
Fig.13
Fig.14
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LLeonetti, G Garcea, HNguyen-Xuan. A mixed edge-based smoothed finite element method (MES-FEM) for elasticity. Computers & Structures, 2016, 173: 123–138 https://doi.org/10.1016/j.compstruc.2016.06.003
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WZeng, G R Liu, C Jiang, TNguyen-Thoi, YJiang. A generalized beta finite element method with coupled smoothing techniques for solid mechanics. Engineering Analysis with Boundary Elements, 2016, 73: 103–119 https://doi.org/10.1016/j.enganabound.2016.09.008
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G RLiu. On partitions of unity property of nodal shape functions: rigid-body-movement reproduction and mass conservation. International Journal of Computational Methods, 2016, 13(2): 1640003 https://doi.org/10.1142/S021987621640003X
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J HYue, M Li, G RLiu, R PNiu. Proofs of the stability and convergence of a weakened weak method using PIM shape functions. Computers & Mathematics with Applications, 2016, 72(4): 933–951 https://doi.org/10.1016/j.camwa.2016.06.002
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G RLiu, G Y Zhang, Y Y Wang, Z H Zhong, G Y Li, X Han. A nodal integration technique for meshfree radial point interpolation method (NI-RPCM). International Journal of Solids and Structures, 2007, 44(11–12): 3840–3860 https://doi.org/10.1016/j.ijsolstr.2006.10.025
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G RLiu, M B Liu. Smoothed Particle Hydrodynamics: A Meshfree Particle Method. Singapore: World Scientific, 2003
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M BLiu, G R Liu. Smoothed particle hydrodynamics (SPH): an overview and recent developments. Archives of Computational Methods in Engineering, 2010, 17(1): 25–76 https://doi.org/10.1007/s11831-010-9040-7
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M BLiu, G R Liu, L W Zhou, J Z Chang. Dissipative particle dynamics (DPD): an overview and recent developments. Archives of Computational Methods in Engineering, 2015, 17(1): 25–76 https://doi.org/10.1007/s11831-010-9040-7
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JLiu, Z Q Zhang, G Y Zhang. A smoothed finite element method (S-FEM) for large-deformation elastoplastic analysis. International Journal of Computational Methods, 2015, 12(4): 1–26 https://doi.org/10.1142/S0219876215400113
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ELi, Z Zhang, C CChang, SZhou, G R Liu, Q Li. A new homogenization formulation for multifunctional composites. International Journal of Computational Methods, 2016, 13(2): 1640002 https://doi.org/10.1142/S0219876216400028
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G RLiu, X Han, Y GXu, K YLam. Material characterization of functionally graded material using elastic waves and a progressive learning neural network. Composites Science and Technology, 2001, 61(10): 1401–1411 https://doi.org/10.1016/S0266-3538(01)00033-1
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G RLiu, X Han, K YLam. Determination of elastic constants of anisotropic laminated plates using elastic waves and a progressive neural network. Journal of Sound and Vibration, 2002, 252(2): 239–259 https://doi.org/10.1006/jsvi.2001.3814
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G RLiu, X Han. Computational inverse techniques in nondestructive evaluation, CRC Press, 2003
212
YLi, G R Liu. An element-free smoothed radial point interpolation method (EFS-RPIM) for 2D and 3D solid mechanics problems. Computers and Mathematics with Applications, 2018, doi: 10.1016/j.camwa.2018.09.047
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G RLiu. A novel pick-out theory and technique for constructing the smoothed derivatives of functions for numerical methods. International Journal of Computational Methods, 2018, 15(3): 1850070 https://doi.org/10.1142/S0219876218500706