Lecture Slides: Lecture Advanced Simulation
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Transcript of Lecture Slides: Lecture Advanced Simulation
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1Challenge the future
G-L-7
Advanced Simulation
Dr. Y. Song (Wolf)Faculty of Industrial Design Engineering
Delft University of Technology
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2Challenge the future
The real & virtual world
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3Challenge the future
The real & virtual world
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4Challenge the future
We need a bridge
Case brief
Compare
Acceptable?
Experience
System
Thought simulation
Experiment
Build abstract model
Solve / simulate
choices
choices choices
choices
do you need more insights/ data?
‘touch’ your thoughts
what are you studying?
what exactly...?
what do you foresee?
what does your model foresee?
did you both agree?everything you did/ saw/ felt/
remember to be true...
Finish!
Revisit choices
Courtesy of centech.com.pl and http://www.clipsahoy.com/webgraphics4/as5814.htm
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5Challenge the future
For simple problems
Water
Drain
Earth
Bathtub
2 2 ( )2 ( ( )) 2 ( )water bathtub orifices d water orificesdh tLength R R h t n C A g h t
dt
Time for empty the
bathtub
Discharge coefficient
Diameter of the hole
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6Challenge the future
NCAP car crash test: VW Golf 6
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7Challenge the future
NCAP car crash test: VW Golf 6
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8Challenge the future
The power of modellingCase study: PAM Crash
ESI® PAM-CRASH®
Cost Safety Prediction Optimization
Courtesy of http://www.esi-group.com/products/crash-impact-safety/pam-crash
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9Challenge the future
Case study: The diving board
Case brief:Design a jump-off diving board for the Olympic game.
Requirement:When the athlete stands still at the tip of the board, the deformation should be between 7~15cm
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10Challenge the future
Analysis
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11Challenge the future
System
System consists of a set of interacting or interdependent system components (or sub-systems)
System
-Structure & interconnectivity-Boundary-Input & Output-Surroundings
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12Challenge the future
The design
System
•Board•Support•Human
Choices: to neglectTemperature differencesHumidity Position of standingNon-uniform MaterialSupporting Structure…
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13Challenge the future
Modelling
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14Challenge the future
The purpose of models
The purpose of models is not to
fit the data but to sharpen the
questions.
Samuel Karlin
National medal of science
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15Challenge the future
Our model: Choices
Support
Fillet
Force
Phenomenon Statics
ModelModel simplification & adjustment
Boundary conditions1. Materials2. Fixture3. Force4. Component interaction
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16Challenge the future
Simulation
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17Challenge the future
Analytical solution of a beam
Area momentum of inertia
Length
Elastic modulus
Force
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18Challenge the future
Analytical solution of the beam
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19Challenge the future
Introducing numerical solutions
2 2 ( )2 ( ( )) 2 ( )water bathtub orifices d water orificesdh tLength R R h t n C A g h t
dt
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20Challenge the future
An example of numerical solutionUsing Euler method to solve an ODE
1 step
3 steps6 steps
12 steps
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21Challenge the future
The Finite Element Method (FEM)
A numerical technique for finding approximate solutions of partial differential
equations (PDE)
Eliminating the differential equation or
rendering the PDE into an ODE
Widely adopted in CAE softwareas
The de facto standard
Ref. http://en.wikipedia.org/wiki/Finite_element_method
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22Challenge the future
FEM
Depending on the validity of the assumptions made in reducing the physical problem to a numerical algorithm, the computer output may provide a detailed picture of the true physical behavior or it may not even remotely resemble it.
Ray W. Clough
Founder of FEMNational medal of science
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23Challenge the future
CAD software
CATIA
Unigraphics
Pro-Engineer
Solidworks
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24Challenge the future
Computer Aided Engineering – Leading Companies
Courtesy of http://www.padtinc.com/blog/post/2011/08/26/CAE_Market_Size.aspx
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The big players - Ansys
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The big players - ESI group
Product UsagePAM Crash
PAM Comfort
ProcessPAM Stamp
Procast
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The big players - COMSOL
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Simulation @ Solidworks®
Aworks
Bs: Simulation
Cs: Solidworks Flow Simulation 2012
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CAE software – The three phases
ning the del and ironmental ors to be lied to it.
e-ocessing Solving
Post processing
The results visualization tools
It is usually performed on high powered computers
Identify, choose
ModelEvaluate
Learn
Cause
Effects
tify, Choose
del Solve/Simulate
Evaluation
Learn
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Elements & Solvers
1 2 3
Selection of elements
Meshing Solver
FEM solution
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Elements & Solvers
1
Selection of elements
FEM solution
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The types of elements Flexibility / Precision
Linear Quadratic Cubic
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mplementation of nodes in Solidworks
Draft quality High quality
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Elements & Solvers
1 2
Selection of elements
Meshing
FEM solution
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Mesh generation
Mesh type
Beam
Shell
Solid
Mixed
Mesh control
► Standard
► Curvature
► Transition
► Local mesh control
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Typical implementation in Solidworks
Beam Shell
Solid
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Solution of the “small” board
Method Result ErrorAnalytical 2.976 E-2 mm 0Beam FEM 2.980 E-2 mm +0.13%Shell FEM 2.961 E-2 mm -0.5%Solid FEM 2.964 E-2 mm -0.4%
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Case study: Mesh control
h generation
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The quality of mesh
► Aspect ratio► Taper► Jacobian ratio► Collapse► Skew angle► Warpage► Twist► …
The quality of mesh
Aspect ratio
Jacobian ratio
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Aspect ratio – An illustration
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Case study: the support
oes matter
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The Jacobian ratio
• Using Jacobian check at Nodes when using p-method
•For high order shells, the Jacobian check uses 6 points located at the nodes
•Empirical study indicates < 40
= 1.0 J = .942 J = .883
= .398 J = -.409 J = -.130
= 1.0 J = .072
he Jacobian calculation is done at the integration points of elements commonly known as Gauss oint. At each integration point, Jacobian Determinant is calculated, and the Jacobian ratio is found by e ratio of the maximum and minimum determinant value.
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The solvers
1 2 3
Selection of elements
Meshing Solver
FEM solution
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Solver selection
Size of the problem. In general, FFEPlus is faster in solving problems with degrees of freedom (DOF) over 100,000. It becomes more efficient as the problem gets larger.
Size of the problem
Computer resources
Material properties
Selection of solver
FEPlus
Direct parse
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Solver selection
Size of the problem
Computer resources
Material properties
Selection of solver
EPlus
rect arse
Computer resources. The Direct Sparse solver in particular becomes faster with more memory availableon your computer.
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Solver selection
Size of the problem
Computer resources
Material properties
Selection of solver
EPls
ect rse
Material properties. When the moduli of elasticity of the materials used in a model are very different (like Steel and Nylon), then iterative solvers are less accurate than direct methods.
The direct solver is recommended in such cases.
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valuation
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The complexity
ools ignore complexity.
Pragmatists suffer it.
Some can avoid it.
Geniuses remove it. Alan Perlis
Computer scientist 1st ACM A.M. Turing Award (1966)
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The influence of choice
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Using sensitivity analysis to evaluate complicated problem
ess
l
Deflection
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The mathematical meaning ofSensitivity analysis
Para
met
e r 1
Para
met
er 2
Para
met
er 3
Input 1
Input 2
Input 3
Output 1
Output 2
Output 3
System
S2
S3
S9
S10
S1
S5
S4
S8
S7
S6
Boundary
S1
S1
SubsystemSurroundings
ent of the metric (f) w.r.t. inputs / parameters (p1,p2...,pn)
)),...,(,),,...,(),,...,( 212121 nnn pppfpppfpppf
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Evaluation
Mesh parameters
Des
ign
para
met
ers
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Reflection
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Reflection
Next iteration
Can we optimize
it?
Can we correct
the error?
it OK?
Mass
Width
Thickness
Length
Material
Choices
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inear Dynamics
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Transient and steady state
Sett
ling
time
band
Mp
Stea
dy-s
tate
er
ror
Transient Steady State
Time ependent
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From Statics to Dynamics
Damping matrix
Mass
Force vector
Stiffness matrix
StaticsStatics
DynamicsDynamics
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Damping – Modal damping
Modal Damping
Modal damping is
defined as a ratio of the
critical damping
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Modal damping ratio
System Viscous Damping RatioMetals (in elastic range) less than 0.01Continuous metal structures 0.02 - 0.04Metal structures with joints 0.03 - 0.07Aluminum / steel transmission lines ~ 0.04Small diameter piping systems 0.01 - 0.02Large diameter piping systems 0.02 -0.03Auto shock absorbers ~ 0.30Rubber 0.05Large buildings during earthquake 0.01 - 0.05Prestressed concrete structures 0.02 -0.05Reinforced concrete structures 0.04 -0.07
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Case study: Slam dunk
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61Challenge the future
Case study: Linear dynamics
A Slam dunk
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62Challenge the future
Non-linear analysis
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63Challenge the future
Structural nonlinearities Courtesy of CAE associations: Snap through bulking
Geometric Nonlinearities
Material Nonlinearities
Contact Nonlinearities
Snap through bulking
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64Challenge the future
Structural nonlinearities Courtesy of CAE associations: Snap through bulking
Geometric Nonlinearities
Material Nonlinearities
Contact Nonlinearities
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65Challenge the future
Material Nonlinearities
Geometric Nonlinearities
Material Nonlinearities
Contact Nonlinearities
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66Challenge the future
Material modelsLinear Elastic Isotropic
Orthotropic
Nonlinear elastic Plasticity
Hyperelasticity
Viscoelasticity
Creep
Nitinol
Material model
...
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67Challenge the future
Time dependent solution
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68Challenge the future
Biomechanics
Courtesy of Daviddarling.info
Complex Beam Theory• Straight Beam• Curved Beam• Composite Beam
Approach from MoM
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69Challenge the future
Case study: Human Joint analysis
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Case study: Bra
Problem:70% of women were wearing a bra that doesn't fit properly
Designer:Dick Powell and Richard Seymour
Technology:Arup's Advanced TechnologyLS-DYNA
Lingerie design
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Computing Fluid Dynamics
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Computing Fluid DynamicsCFD
branch of fluid mechanics that es numerical methods and algorithms to lve and analyze problems that involve fluid ws.
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Case study: Air drag
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Drag coefficienthttp://en.wikipedia.org/wiki/Automobile_drag_coefficient
2
21 vCAF d
agN]
Drag Coefficient
Area[m2]
Density[kg/m3]
Velocity[m/s]
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Drag coefficienthttp://en.wikipedia.org/wiki/Automobile_drag_coefficient
Cd =0.26
Audi A4 B5 1995
BMW 7-series 2009
Honda Civic (Sedan) 2006
Peugeot 307 2001
Porsche 997 Turbo/GT3 2006
Volkswagen GTI Mk IV 1997
Nissan 370Z Coupe(0.29 with sport package)
2009 [16]
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Case study: Pointy or round?
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Case study: Air drag – Low speedAt 120 km/hour, which design is faster?
P2P1
79N41N
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Case study: Supersonic
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Case study: Air drag – Supersonic At 350 m/s, which design is faster?
9292N8966N
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Case study: Drafting
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What is drafting?
Drafting or slipstreaming is technique where two
ehicles or other moving bjects are caused to align
n a close group reducing he overall effect f drag due to exploiting the
ead object's slipstream.
Drafting
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Air drag
High Pressure- Air is compressed
Low pressure – a bit vacuum
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To reduce air drag
Reduce the pressure here
Increase the pressure here
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Drafting
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Relations with in-between distance
L
mm) Air Drag Cylinder 1 (N)
Air Drag Cylinder 2 (N)
40 0.292 0.06
50 0.291 0.09
60 0.288 0.115
70 0.266 0.141
80 0.276 0.15
5
5
2
5
3
5
Drag of the cylinder behind
Drag of the cylinder front
Drag of the cylinder (no drafting)
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Who taught swan goose aerodynamics?
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atural convection
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Natural convection
eat wine by natural convection
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ase study: Karman Vortex Street
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Seattle
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There is a bridge
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Tacoma narrow bridge
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Tacoma narrow bridge 1940
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Case study: Karman Vortex Street
Theodore von Karman
epeating pattern of swirling vortices caused by the steady separation of flow of a fluid around blunt dies
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Case study: Karman Vortex Street
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Cell mesh in Flow Works
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otation
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Parrot AR Drone
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Simulation
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ase study: Fluid structure nteractions (FSI)
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The Senz Mini model
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The Senz Mini flow simulation
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FSI in different ways
Fluid
Time interval 1
Time interval 2
Time interval …
Time interval n
Structure
Time interval 1
Time interval 2
Time interval …
Time interval n
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SW - Think before we start
Relative Stable
Time interval 1
Time interval 2
Time interval …
Time interval n
Changed
Time interval 1
Time interval 2
Time interval …
Time interval n
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Non-linear: Results
Real Test
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Theodore von Karman
cientists study the world as it is,
ngineers create the world that
ver has been.
Theodore von Karman
National medal of science
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At least we can
ou can't make it good, at least
ke it look good.
Bill Gates
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hank You!
Dr. Y. Song (Wolf)Faculty of Industrial Design Engineering