Abstract

Due to the number of layers and their respective geometrical complexities, finite element analyses of flexible pipes usually require large-scale schemes with a high number of elements and degrees-of-freedom. If proper precautions are not taken, such as suitable algorithms and numerical methods, the computational costs of these analyses may become unfeasible. Finite macroelements are finite elements formulated for the solution of a specific problem considering and taking advantage of its particularities, such as geometry patterns, to obtain computational advantages, as reduced number of degrees-of-freedom and ease of problem description. The element-by-element (EBE) method also fits very well in this context, since it is characterized by the elimination of the global stiffness matrix and its memory consumption grows linearly with the number of elements, besides being highly parallelizable. Over the last decades, several works regarding the EBE method were published in the literature, but none of them directly applied to flexible pipes. Due to the contact elements between the layers, problems with flexible pipes are usually characterized by very large matrix bandwidth, making the implementation of the EBE method more challenging, so that its efficiency and scalability are not compromised. Therefore, this work presents a parallelized implementation of an element-by-element architecture for structural analysis of flexible pipes using finite macroelements. Four synchronization algorithms were developed and analyzed in detail, including their scalability assessment, and comparisons were made with a well-established finite element method (FEM) software with significant gains in simulation time and memory consumption.

References

1.
Provasi
,
R.
,
2013
, “
Contribuição ao Projeto de Cabos Umbilicais e Tubos Flexíveis: Ferramentas de CAD e Modelo de Macro Elementos
,” Ph.D. thesis, São Paulo, Brazil.
2.
Provasi
,
R.
, and
Martins
,
C. A.
,
2013
, “
A Finite Macro-Element for Orthotropic Cylindrical Layer Modeling
,”
ASME J. Offshore Mech. Arct. Eng
,
135
(
3
), p.
031401
.
3.
Provasi
,
R.
, and
Martins
,
C. D. A.
,
2014
, “
A Three-Dimensional Curved Beam Element for Helical Components Modeling
,”
ASME J. Offshore Mech. Arct. Eng.
,
136
(
4
), p.
041601
.
4.
Provasi
,
R.
, and
Martins
,
C. A.
,
2013
, “
A Rigid Connection for Macro-Elements With Different Node Displacement Natures
,”
The Twenty-Third International Offshore and Polar Engineering Conference
,
Anchorage, AK
,
June 30–July 5
, International Society of Offshore and Polar Engineers (ISOPE).
5.
Provasi
,
R.
,
Toni
,
F. G.
, and
Martins
,
C. A.
,
2018
, “
A Frictional Contact Element for Flexible Pipe Modelling With Finite Macroelements
,”
ASME J. Offshore Mech. Arct. Eng.
,
140
(
5
), p.
051703
.
6.
Toni
,
F. G.
,
2014
, “
Ferramenta Eficiente para Análise Estrutural de Tubos Flexíveis Usando Macroelementos Finitos
,” Projeto de Conclusão de Curso, Escola Politécnica da Universidade de São Paulo.
7.
Toni
,
F. G.
, and
Martins
,
C. A.
,
2017
, “
Parallelized Element-by-Element Architecture for Structural Analysis of Flexible Pipes Using Macro Finite Elements
,”
ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering
,
Trondheim, Norway
,
June 25–30
, pp.
1
11
.
8.
Hughes
,
T. J. R.
,
Levit
,
M. A. I.
, and
Winget
,
J.
,
1983
, “
Element-by-Element Implicit Algorithms for Heat Conduction
,”
J. Eng. Mech.
,
109
(
2
), pp.
576
585
.
9.
Hughes
,
T. J. R.
,
Levit
,
I.
, and
Winget
,
J.
,
1983
, “
An Element-by-Element Solution Algorithm for Problems of Structural and Solid Mechanics
,”
Comput. Methods Appl. Mech. Eng.
,
36
(
2
), pp.
241
254
.
10.
Winget
,
J. M.
, and
Hughes
,
T. J. R.
,
1985
, “
Solution Algorithms for Nonlinear Transient Heat Conduction Analysis Employing Element-by-Element Iterative Strategies
,”
Comput. Methods Appl. Mech. Eng.
,
52
(
1–3
), pp.
711
815
.
11.
Hughes
,
T. J. R.
,
Ferencz
,
R. M.
, and
Hallquist
,
J. O.
,
1987
, “
Large-Scale Vectorized Implicit Calculations in Solid Mechanics on a Cray X-MP/48 Utilizing EBE Preconditioned Conjugate Gradients
,”
Comput. Methods Appl. Mech. Eng.
,
61
(
2
), pp.
215
248
.
12.
Carey
,
G. F.
, and
Jiang
,
B.-N.
,
1986
, “
Element-by-Element Linear and Nonlinear Solution Schemes
,”
Commun. Appl. Numer. Methods
,
2
(
2
), pp.
145
153
.
13.
King
,
R. B.
, and
Sonnad
,
V.
,
1987
, “
Implementation of an Element-by-Element Solution Algorithm for the Finite Element Method on a Coarse-Grained Parallel Computer
,”
Comput. Methods Appl. Mech. Eng.
,
65
(
1
), pp.
47
59
.
14.
Levit
,
I.
,
1987
, “
Element by Element Solvers of Order N
,”
Comput. Struct.
,
27
(
3
), pp.
357
360
.
15.
Hughes
,
T. J. R.
, and
Ferencz
,
R. M.
,
1988
, “Fully Vectorized EBE Preconditioners for Nonlinear Solid Mechanics: Applications to Large-Scale Three-Dimensional Continuum, Shell and Contact/Impact Problems,”
Domain Decomposition Methods for Partial Differential Equations
,
R.
Glowinski
, et al
, ed.,
SIAM
,
Philadelphia
, pp.
261
280
.
16.
Adeli
,
H.
, and
Kumar
,
S.
,
1995
, “
Distributed Finite-Element Analysis on Network of Workstations—Algorithms
,”
J. Struct. Eng.
,
121
(
10
), pp.
1448
1455
.
17.
Gullerud
,
A. S.
, and
Dodds Jr.
,
R. H.
,
2001
, “
MPI-Based Implementation of a PCG Solver Using an EBE Architecture and Preconditioner for Implicit, 3-D Finite Element Analysis
,”
Comput. Struct.
,
79
(
5
), pp.
553
575
.
18.
Thiagarajan
,
G.
, and
Aravamuthan
,
V.
,
2002
, “
Parallelization Strategies for Element-by-Element Preconditioned Conjugate Gradient Solver Using High-Performance Fortran for Unstructured Finite-Element Applications on Linux Clusters
,”
J. Comput. Civil Eng.
,
16
(
1
), pp.
1
10
.
19.
Liu
,
Y.
,
Zhou
,
W.
, and
Yang
,
Q.
,
2007
, “
A Distributed Memory Parallel Element-by-Element Scheme Based on Jacobi-Conditioned Conjugate Gradient for 3D Finite Element Analysis
,”
Finite Elem. Anal. Des.
,
43
(
6–7
), pp.
494
503
.
20.
Kiss
,
I.
,
Gyimothy
,
S.
,
Badics
,
Z.
, and
Pavo
,
J.
,
2012
, “
Parallel Realization of the Element-by-Element FEM Technique by CUDA
,”
IEEE Trans. Magn.
,
48
(
2
), pp.
507
510
.
21.
Kiss
,
I.
,
Badics
,
Z.
,
Gyimothy
,
S.
, and
Pavo
,
J.
,
2012
, “
High Locality and Increased Intra-Node Parallelism for Solving Finite Element Models on GPUs by Novel Element-by-Element Implementation
,”
2012 IEEE Conference on High Performance Extreme Computing (HPEC)
,
Waltham, MA
,
Sept. 10–12
, pp.
1
5
.
22.
Martínez-Frutos
,
J.
, and
Herrero-Pérez
,
D.
,
2015
, “
Efficient Matrix-Free GPU Implementation of Fixed Grid Finite Element Analysis
,”
Finite Elem. Anal. Des.
,
104
, pp.
61
71
.
23.
Martínez-Frutos
,
J.
,
Martínez-Castejón
,
P. J.
, and
Herrero-Pérez
,
D.
,
2015
, “
Fine-Grained GPU Implementation of Assembly-Free Iterative Solver for Finite Element Problems
,”
Comput. Struct.
,
157
, pp.
9
18
.
24.
Saad
,
Y.
,
2003
,
Iterative Methods for Sparse Linear Systems
, 2nd ed.
SIAM
,
Philadelphia, PA.
25.
Toni
,
F. G.
, and
Martins
,
C. A.
,
2020
, “
Parallelized Element-by-Element Solver for Structural Analysis of Flexible Pipes Using Finite Macroelements
,”
Proceedings of the ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering Pipelines, Risers, and Subsea Systems), Vol. 4
,
Virtual, Online
,
Aug. 3–7
, ASME, pp.
1
20
.
You do not currently have access to this content.