3-6 September 2013 Cagliari, Sardinia, Italy

The Fourteenth International Conference on Civil, Structural and Environmental Engineering Computing

3-6 September 2013 Cagliari, Sardinia, Italy

Enhanced Mesoscale Partitioned Modelling for Unreinforced Masonry Structures

L. Macorini - B.A. Izzuddin

Computational Structural Mechanics GroupDepartment of Civil and Environmental Engineering

Imperial College London, UK

OutlineAdvanced modelling for URM

Mesoscale Partitioned Modelling

Domain Partitioning approach

Enhanced Mesoscale Partitioned Modelling for Unreinforced Masonry Structures 1/28

3D Mesoscale model

Conclusions

Enhancements to improve efficiency

Mesoscale modelTwo-material approach

Mesoscale scale

Advanced modelling for URM


(Massart, 2007)

• Mesoscale descriptions for URM guarantee accurate response prediction

• Detailed mesoscale models are usually computationally demanding

Mesoscale Partitioned Modelling

Structural scaleSolid elements and 2D nonlinear interfaces

An advanced 3D mesoscale model is combined with partitioning approach

• Partitioning approach with super-elements for masonry

• Parallel computing


2D nonlinear interface element

t

ts

ss<0

Gf,II

ux(y)

stanf

t

C

Gf,I

uz

st

s s

s

sc

ss

suz

Gc

3D mesoscale model for nonlinear analysis under extreme loading

Shear test

Compression test

• Multi-surface nonassociated plasticity

• Geometric nonlinearity


In-plane behaviourVermeltfoort AT, Raijmakers TMJ (1993)

J4D J5D

pv=0.3 MPamortar

interface

mortar interface

brick interface




J4D J5D

Wpl1Wpl1Wpl1Wpl1

Wpl2

pv=0.3 MPa




Wpl1

Wpl2

Nonlinear Analysis of Masonry Structures using Mesoscale Partitioned Modelling 7/28


Out-of-plane behaviourChee Liang, N.G. (1996)

Wpl1Wpl1Wpl1

Nonlinear Analysis of Masonry Structures using Mesoscale Partitioned Modelling 8/28


0 0.3 0.6 0.9 1.2 1.5 1.8 [mm]

0

10

20

30

40

Fh [

kN/m

2 ]

Exp. - wall 8Exp. capacityProposed model

wall 8

wall 12

Mesoscale analysis of large URM components

Gattesco et al. (2008)



Mesoscale analysis to represent quasi-brittle behaviour

A)

B)

• Dynamic analyses with a large number of time steps are used for representing post-peak response


0.0 1.0 2.0 3.0 4.0 5.0 6.0

h [mm]

0

20

40

60

80

100

F h [

kN]

Exp. [21]ADAPTIC

A

B


Domain partitioning approach


Domain partitioning approach

Communication between parent structure and partitions

MPI


Detailed analysis of large structuresDomain partitioning approach

162840 nodes – 62 partitions

sm [MPa] Wpl1m [MPa]




• When analysing large URM structures, the most critical process becomes that of the parent structure. This may significantly reduce efficiency leading to an excessively long wall-clock time.

162840 nodes 62 partitions



• Enhancements to improve efficiency: - Hierarchic partitioning - Mixed-dimensional coupling

162840 nodes 62 partitions

Enhancements to improve efficiencyEnhanced domain partitioning approach

• Modelling with hierarchic partitioning (Jokhio 2012)



• Modelling with partitions and master-slave coupling (Jokhio 2012)

6 DoF

Mixed-dimensional coupling



• Modelling heterogeneous structures with URM

Infilled frame


Elasto-plastic beam elements are used for modelling beams and columns of the frame, while the detailed mesoscale description is utilised for URM panels

Numerical examplesEnhanced domain partitioning approach

• Numerical performance (Speed-up)

Elastic analysis of a large URM wall (48 48 20-noded solid elements)

Prescribed top vertical displacements in 1 step and top horizontal displacements in 10 steps


uz ux

Numerical examplesEnhanced domain partitioning approach

• Numerical performance (Speed-up)


Standard (flat) Partitioning Approach

Enhanced Partitioning Approach (hierarchic partitioning)

P-L1

P-L2


Numerical examples

Enhanced domain partitioning approach

• Numerical performance – Speed-up


model N. processors

Parent Struct.DOFs

Part. L1DOFs

Part. L2DOFs S

m 1 142848 - - -P4 5 2304 36864 - 4.60

P16 17 6912 9792 - 6.96P64 65 16128 2736 - 3.24

P4 mslc 5 576 36864 - 3.73P16 mslc 17 1728 9792 - 12.43P64 mslc 65 4032 2736 - 116.39

P44 20 768 2304 9792 14.40

P416 69 768 2304 2736 28.65P44 mslc 20 96 576 9792 17.63

P4x16 mslc 69 96 576 2736 205.50

Si= Tm/TSi

Tm = 13152 s


flat partitioning

Numerical examples




0

1

2

3

4

5

6

7

8

0 10 20 30 40 50 60 70

Spe

ed-u

p S

N. of processors

P-L1


Si= Tm/TSi

Tm = 13152 s

Flat partitioning

Numerical examples




model N. processors

Parent Struct.DOFs

Part. L1DOFs

Part. L2DOFs S

m 1 142848 - - -P4 5 2304 36864 - 4.60

P16 17 6912 9792 - 6.96P64 65 16128 2736 - 3.24

P4 mslc 5 576 36864 - 3.73P16 mslc 17 1728 9792 - 12.43P64 mslc 65 4032 2736 - 116.39

P44 20 768 2304 9792 14.40

P416 69 768 2304 2736 28.65P44 mslc 20 96 576 9792 17.63

P4x16 mslc 69 96 576 2736 205.50

Si= Tm/TSi

Tm = 13152 s


flat partitioning with mixed-dimensional couplinghierarchic partitioning hierarchic partitioning with mixed-dimensional coupling




Si= Tm/TSi

Tm = 13152 s



• Solution accuracy: partitioned vs. monolithic model

Normal stresses after the application of the vertical displacement



• Solution accuracy: partitioned vs. monolithic model

Normal stresses at the end of the analysis


Numerical examples


• Analysis of heterogeneous structures under extreme loading


Numerical examples




Blast pressure in time

Model validation under blast loading (Macorini and Izzuddin 2013)

Numerical examples




Conclusions


When using hierarchic partitioning and master-slave coupling, contrary to the case of flat partitioning, computational efficiency is preserved also in the analysis of URM structures modelled using a large number of partitions

In the case of master-slave coupling the gain in computational performance is obtained losing accuracy depending upon the specific loading conditions

This limitation will be overcome in next enhancements by introducing soft coupling using a Lagrangian multiplier approach

AcknowledgementsThe authors gratefully acknowledge the High Performance Computing (HPC) Services at Imperial College London for providing and supporting the required computing facilities.

Enhanced Mesoscale Partitioned Modelling for Unreinforced Masonry Structures

3-6 September 2013 Cagliari, Sardinia, Italy

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