meditech june meetings/17thjune 2008...young’s modulus yield newtonian fluid non-newtonian fluid...

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Measurements and Input for Biomechanical SimulationBrian Walker

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Bridging the gap

This meeting will include speakers from the areas of biology, biosciences and biomechanics

and will explore and demonstrate new developments and tools which are now available for

solving many problems which link these disciplines. Here for instance, mechanotransduction,

tissue engineering and nano/micro/macro models of biological structures are some of the

new areas where collaboration between the biosciences, engineering and computer

technologies are proving to be particularly fruitful. It is the aim of this meeting to focus on

bridging the gap between biologists and bioengineers by providing examples of applications

and explanations of how the various scientific tools now being developed, can be

successfully applied in practice.

Biologists Bioengineers

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Where are we now?

Engineers

Biologists

Clinicians

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Outline

Advanced mechanical computer simulation

Examples in bio-engineering

Modelling the shaken baby syndrome

Eye model -

Data from Imaging software

Head and neck model

Data from Imaging software

Sharp force study

Material investigation of a biosimulant

Auxetic foam

Small scale modelling

Future and challenges in bio-engineering

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Terminology Solution Methods Lagrange

Euler

Arbitrary Lagrangian-Eulerian (ALE)

Smooth Particle Hydronamic (SPH)

Element Free Gerlekin (EFG)

Computational Fluid Dynamics (CFD)

Strains Engineering Strain

True Strain

Volumetric Strain

Plane Strain

Green-Lagrange Strain

Green-Saint Venant Strain

Stresses Von-Mises Stress

Principal Stress

Stress Invarients

1st Piola-Kirchhoff Stress Tensor

2nd Piola-Kirchhoff Stress Tensor

Plane Stress

Material Models Elastic

Orthotropic Elastic

Arruda Boyce

ViscoElastic

Non-Linear Elastic

Hyper Elasticity

Plastic Kinematic Poissons Ratio

Youngs Modulus

Yield

Newtonian Fluid

Non-Newtonian Fluid

Hardening Modulus

NOT

TODAY

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Oasys LS-DYNA Environment Software

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LS-DYNA best known for

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LS-DYNA best known for

Typical state of the art vehicle crash model includes:

Sheet metal structure steel or aluminium

Connections eg. spotwelds, seamwelds, rivets (SPR), bolts

Glazing

Power train - engine, gear box, etc.

Wheels, tyres, suspension

Seats including frame and foam

Occupant models (models of bio-fidelic test dummies)

Restraint systems airbags and seatbelts

Sensors and accelerometers

Crash barriers (honeycomb)

Model Size

2,500,000 elements

Event time 120 250 ms

Analysis time 16 hours on 16 cpus

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LS-DYNA best known for

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LS-DYNA best known forEarly 1990s

25,000 elements

2007

2,500,000 elements

Image courtesy of Jaguar Cars

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LS-DYNA Main features

Extensive element library

Complex contact algorithms

Over 200 constitutive models

Explicit and Implicit Time Integration Schemes

Lagrange, ALE, Euler and meshless methods

Fluid Structure Interaction

Non-Linear Dynamics, Large Deformation

MPP job can run simultaneously on many processors allowing large complex problems to be solved

Thermal analysis coupled to structural analysis

Navier-Stokes compressible and incompressible fluid flow being added Multi Physics

Simulation

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LS-DYNA Material Models

LS-DYNA has a library of over 200 constitutive models. Many of these are

suitable for use in biomechanical modelling. Examples include:

Piecewise Linear Plasticity

Plastic Kinematic

Johnson Cook

Various Rubber models

Various Foam models

Various Concrete models

Fabric

Honeycomb

Composites

Elastic

Isotropic, Orthotropic, Anisotropic

Mooney-Rivlin

Viscoelastic

Non-linear orthotropic

General Viscoelastic (Maxwell model)

Orthotropic Viscoelastic

Soft tissue

Arruda Boyce

Heart Tissue

Lung Tissue

Quasilinear Viscoelastic

Rigid

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Modelling Stages

Geometry

Scan

Measure

Boundary Conditions

Restraints

Constraints

Loading

Prescribed motion

Constitutive Modelling

Choose appropriate material model

Get material constants to use

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LS-DYNA

SCAN

MESH

SET-UP

ANALYSE

POST-PROCESS

Oasys Software + Simpleware

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Scanning

LS-DYNA Model

+ScanFE

Meshing & Material Properties

+ScanCAD

CAD import &

positioning

ScanIPImageProcessing

CT, Micro-CT, MRI, Tiff, Jpg ..etc.

Simpleware

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Modelling the Shaken Baby Syndrome Study I Sheffield University, Department of Mechanical Engineering. I. Howard, E. Patterson and

co workers. 2001

Physical child abuse is common

In UK estimated that 200 infants may die from brain injuries arising from violent shaking.

Perhaps 400 survive with severe mental & physical disability

Damage to the retina (light sensitive part of eye)

Is often found in shaken babies together with brain injuries

Combined brain and eye injuries are rare in severe accidental head trauma

Ophthalmology Pictures of Retinal

Haemorrhages (shown as dark spots) in the Eyes of Shaken Babies [Habib, N E Visual Loss from Bungee Jumping. Brit. J.

Ophthalmology, 343(8895), P487, 1994 ]

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Study included:

Test work - volunteers asked

to shake nine month old baby to exhaustion (typically 20 seconds)

to shake as violently as possible [10g

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Skull [E=6500MPa u=0.2 r=1500kg/m3 t=10mm ]

Cerebrospinal fluid [E=0.1MPa u=0.49 r=1040kg/m3 G=0.5MPa]

Brain [E=0.675MPa u=0.49 r=1040kg/m3 G=1.68MPa]

Skull and brain model

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Four components

Eye socket (red)

[E=6500MPa o.d.=30mm ]

Retina (not visible)

[E=20kPa =1050kg/m3]

Sclera (purple)

[E=100MPa =2000kg/m3 o.d.=24mm ]

Vitreous (blue)

[E=10kPa =1040kg/m3 o.d.=22mm p=13.2kPa]

Eye model

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Max. stress in retina during 1st cycle Brain Shear stress

Displacements of Sclera

equator (forced)

poles (free)

Initial results showed:

Retina is susceptible to accumulative stress during shaking cycles

Pressure in brain increases with repeated shaking

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Modelling the Shaken Baby Syndrome Study IISheffield University, Department of Mechanical Engineering. J Rowson, D Batterbee, 2008

To study the hypothesis That infants are more susceptible to SBS

due to the presence of the fontanelle

As the brain cavity is not rigidly enclosed, damage to the brain and

surrounding tissues is more likely

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Initial aim of present work

To validate Fluid Structure Interaction (FSI) models using

more formal methods e.g. using various sinusoidal

excitations of different amplitude and frequency

Cerebrospinal fluid

320 Solid Elements

MAT Elastic_Fluid

Brain

768 Solids

MAT Elastic

Fontanelle

8 Shells

MAT ElasticSkull

56 Shells

Rigid

Fluid elements have Lagrangian formulation i.e. nodes move and deform with the material

Nodes between fluid and surrounding parts are merged i.e. contact definitions are not required

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Eye Model

Data acquisition

Segmentation

FE and STL model generation

Impact simulation in

LS-DYNA

Patient specific computer models of the human eye based on in vivo MRI

acquisitions were constructed

Bio-fidelic three dimensional numerical meshes of the orbital area

including the eye and surrounding soft and hard tissues generated

Impact with projectile modelled using LS-DYNA

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A 29 year Caucasian female

Models constructed based on two high

resolution MRI scans of the right orbital area (using head coil and surface coil)

In-plane and out-of-plane resolution of 1mm. The data consisted of 50 slices, each at a pixel resolution of 128x128

Transparent top view of model showing

each mask including bone, skin, globe, fatty tissue and muscles

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Segmentation within ScanIP

6 different segmented structures

Globe and optic nerve

Bony orbit

Eyelids

Fat

Facial soft tissues

Extra-ocular muscles

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Volume mesh: mixed hex/tet elements or pure tet.

Structures/parts modelled either as volumetric meshes or as surface meshes as

required (e.g. the bony orbit modelle

Recommended

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