simulia-update-sph cel.pdf
TRANSCRIPT
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SIMULIA / Abaqus / Engineous
- ein Update
Martin KssnerDassault Systemes Simulia GmbH
Content
Integration of processes Multiphysics Unified FEA Parallelization Material laws Simulation Lifecycle Management Optimization/Robust Design Conclusion
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Integration of processes
FEA is not all that is out there .
Innovation Integration ProcessCentered on Virtual Experience
Automotive
Aerospace
Shipbuilding
Industrial Equipment
High Tech
Consumer Goods
Consumer Packaged Goods
Life Sciences
Energy
Construction
Business Services
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Multiphysics
There is more that matters than just
stresses and strains
StructuralStructural
Multiphysics in Abaqus Unified FEA
Abaqus enables coupling of multiple fields
Thermal
Pore pressure
Electrical
Piezo-electrical
Acoustics
Fluid flow
Structural
Courtesy: Honeywell FM&T
Courtesy of Dr. Michelle Hoo Fatt (University of Akron)
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Coupled Eulerian-Lagrangian (CEL)
Enhances the ability of Abaqus/Explicit to model fluids and materials that undergo extreme deformation
Capability consists of:A three-dimensional Eulerian
element typeSupport for all materials in
Abaqus/Explicit except hyperelasticity and anisotropy
General contact between Eulerian and Lagrangian domains
Parallel processingTarget applications include:
Hydroplaning, water impact, earth penetration, sloshing, bird strike
Fully supported in Abaqus/CAE
Volume fraction tool being used to fill a bottle for a drop test
Coupled Eulerian-Lagrangian (CEL)
Uses a multi-material finite element formulation Volume-of-fluids method tracks material boundaries within an
Eulerian domain Conforming meshes are not required
Provides a specialized technique to simulate FSI problems that include:
Complex structural contact conditions including self-contact Large structural deformations and displacementsVery high-speed dynamicsDamage, failure, or erosion at the fluid-structure interface
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Coupled Eulerian-Lagrangian (CEL)
Example: Hydroplaning When a vehicle is driving in the rain, water trapped between the
road and tire leads to pressure build-up and possible loss of traction Tire manufacturers use simulation to design tread patterns that
reduce the possibility of hydroplaning CEL easily handles the complex contact conditions (pinching) that
occur during hydroplaning simulation
Unified FEA
Re-Using instead of Re-Doing
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Implicit/explicit integration
Unified FEA is a key component of our product strategy Implies the ability to easily transfer models and results
between implicit and explicit solution technologies Implicit/explicit integration
Most elements and materials that are common to both solution technologies can be transferred
Nonlinear Dynamics
Abaqus/Standard (=Implicit) Uses a second-order accurate, implicit scheme called the Hilber-
Hughes-Taylor (HHT) rule. This is a generalization of the Newmark method.
Second-order accurate means the scheme integrates a constant acceleration exactly.
The method is unconditionally stable: any size time increment can be used, and the solution will remain bounded.
Abaqus/Explicit (=Explicit) Uses a second-order accurate, explicit integration scheme. The method is conditionally stableit gives a bounded solution only
when the time increment is less than a critical value.
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Comparing implicit and explicit
integration scheme
Implicit
Time increment size is not limited: generally fewer time increments required to complete a given simulation.
Each time increment is expensive since each requires the solution for a set of simultaneous equations.
Explicit
Time increment size is limited: generally many more time increments are required to complete a given simulation.
Each time increment is relatively inexpensive because not required to solve a set of simultaneous equations.
Most of the computational expense is associated with element calculations (forming and assembling I).
The model is in equilibrium at the beginning and end of the increment
Seek to control the residual at an intermediate point
Residual at half-increment (half-step residual)
Implicit Ideal for problems where the
response period of interest is long compared to the vibration frequency of the model.
Difficult to use explicit dynamics effectively because of the limit on the time increment size.
Use for problems that are mildly nonlinear and where the nonlinearities are smooth (e.g., plasticity).
With a smooth nonlinear response Abaqus/Standard will need very few iterations to find a converged solution.
Explicit Ideal for high-speed dynamic
simulations Require very small time
increments; implicit dynamics inefficient.
Usually more reliable for problems involving discontinuous nonlinearities.
Contact behavior is discontinuous and involves impacts, both of which cause problems for implicit time integration.
Other sources of discontinuous behavior include buckling and material failure.
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Abaqus/Standard
Comprehensive linear & nonlinear implicit general purpose finite element analysis of structural, thermal, acoustic & mechanism simulations
Integration with Abaqus/Explicit provides maximum flexibility for multi-physics simulation (Unified FEA)
Sophisticated contact, failure, material modeling & other advanced nonlinear capabilities
High-performance direct and iterative solvers with support for shared and distributed memory configurations
Powerful interfaces for user customization
Abaqus/Explicit
Comprehensive explicit finite element analysis of structural, thermal, acoustic & mechanism simulations
Integration with Abaqus/Standard provides maximum flexibility for multi-physics simulation (Unified FEA)
High-performance solver with support for shared and distributed memory configurations
Powerful interfaces for user customization
Courtesy BMW
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Abaqus Unified FEA
Abaqus import capability can transfer a model or part of a model, together with associated state information, between an Abaqus/Explicit analysis and an Abaqus/Standard analysis
Abaqus/Explicit
Abaqus/Standard
Abaqus/Explicit
Abaqus/Standard
Abaqus/Explicit
Abaqus/Standard
Overlapping material library
Damage and failure of fiber-reinforced composites Example: Hashins damage initiation criterion of
unidirectional composites is available in Abaqus/Standard and Abaqus/Explicit
The model captures four different damage mechanisms
Fiber rupture Fiber buckling and kinking Matrix cracking Matrix crushing
Damage evolution consistent with damage framework introduced in Version 6.5
Abaqus/Explicit Abaqus/Explicit and Abaqus/Standard Abaqus/Explicit import
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Example (Payload Fairing)
Pressure load = 20 x (cos2) ) ) ) psi under side only
Note : strain discontinuities in doubler region
Example (Payload Fairing)
Composites supported in both /Standard and /Explicit solver/Standard (20 psi) /Explicit (20 psi)
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Example (Payload Fairing)
Composites supported in both /Standard and /Explicit solver/Standard (20 psi) /Explicit (20 psi)
Example (Payload Fairing)
Analysis in /Explicit carried out to collapse of structureApplied Load = 50 psi over 1.0 second
P = 42.5 psi (t = 0.85)
Nose Tip Displacement
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Parallelization
We need to become MUCH faster .
Parallelization and performance
DMP direct sparse solver Scalability significantly improved Memory use noticeably reduced
when running on 4 or more compute nodes
Unsymmetric solver now supported (important for contact simulations)
Multiple linear loads cases and Riks method now supported
DMP is an effective strategy for Abaqus/Standard
Courtesy of the DANA Corporation
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Major Breakthrough in Abaqus Performance
Expanded procedure support Improved scalability Reduced memory requirements
92%Speed Up
Courtesy DANA 9.2M DOF
Material Laws
Things became really difficult .
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Material law
The calibration of the second invariant of the deviatoric left Cauchy-Green tensor causes troubles when calibrating hyperelastic material law.
What to do with these kind of information?
Simulation Lifecycle Management
What to do with all the data and how to
store the processes.?
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Simulation Lifecycle Management
SLM means: Bringing Order to Simulation:
Management of Data, Methods and Processes Connecting users to each other and the enterprise
Leveraging Simulation IP: Capturing simulation know-how and related decisions Extracting and re-using the built-in value of simulation activity
An Open Platform to Manage and Deploy Applications: Workflow chaining and job submission Connector architecture for 3rd party applications
SLM Sneak Preview
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1. 3DSearch2. 3DCompass3. 3DNavigation4. 3DHeads-Up5. Contextual
Buddy List
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Optimization / Robust Design
Isight for Abaqus: Benefits
Reduce design time Execute multiple simulation studies automatically overnight Parallel submission of optimization, Monte Carlo, and DOE jobs on
multiprocessor machines or in conjunction with LSF Improve quality
Design-to-target for simulation attributes Account for variation in materials, loads, tolerances, and operating
conditions Find the best design
Understand which model parameters drive targets
Trade off design alternatives in real time with colleagues and other stakeholders
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The Big Picture Automated Design Strategies
Y1
ConstraintBoundary
Y2
Initial Best Design
Feasible Infeasible (safe) (failed)
X2
X1
Outputs
Inputs
Shop for the best design
DOE:
Critical Factors
and Initial Design
Isight for Abaqus: Design of Experiments (DOE)
Perform trade-offs and understand the design space Capabilities
Determine which input variables have the most influence on your simulation outputs
Use to build approximation models
Estimate of an Optimal Design
Types Parameter Studies
Orthogonal Arrays
Full Factorial Arrays
Optimal Latin Hyper Cube
Latin Hyper Cube
Central Composite
Import Outside Experiments
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Isight for Abaqus: Approximations
Build from DOE samples, speed up calculations from Six Sigma, speed up live performance tradeoffs Types
Response Surface Model (to 4th order) Radial Basis Function (RBF)
Capabilities Automatic setup Automatic error estimation Effects graphs Interactive tradeoffs Simulation Surrogate
The Big Picture Automated Design Strategies
Y1
ConstraintBoundary
Y2
Initial Designfrom DOE
Feasible Infeasible (safe) (failed)
Outputs
Improve Design Performance
Optimization(Approximations)
Optimized Design
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Isight for Abaqus: Optimization
Drive toward a target performance Capabilities
Formulate variables, constraints, and multiple objectives
Multi-objective Pareto fronts Types
Gradient: NLPQL Multi-Objective: NCGA, AMGA Pattern: Hooke-Jeeves and Downhill Simplex
Exploratory: Multi-Island Genetic Algorithm(MIGA), Adaptive Simulated Annealing (ASA)
Automatic Optimization: Pointer Automatically configures NLPQL, an evolutionary algorithm, Downhill Simplex, and a linear solver
Sim approximation surrogate
The Big Picture Automated Design Strategies
Y1
ConstraintBoundary
Y2
Feasible Infeasible (safe) (failed)
Outputs
Improve Design Quality
Design for Six Sigma
Robustness and Reliability Analysis and Optimization
Robust and ReliableDesign
% Unreliable% Reliable
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Conclusion
SIMULIA / Abaqus / Engineous
- ein Update
Martin KssnerDassault Systemes Simulia GmbH