SIMULIA-Update-SPH CEL.pdf

SIMULIA / Abaqus / Engineous

- ein Update

Martin KssnerDassault Systemes Simulia GmbH

[email protected]

Content

Integration of processes Multiphysics Unified FEA Parallelization Material laws Simulation Lifecycle Management Optimization/Robust Design Conclusion

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

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)

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


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


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

11

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.

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.

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

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

Example (Payload Fairing)

Pressure load = 20 x (cos2) ) ) ) psi under side only

Note : strain discontinuities in doubler region


Composites supported in both /Standard and /Explicit solver/Standard (20 psi) /Explicit (20 psi)


Composites supported in both /Standard and /Explicit solver/Standard (20 psi) /Explicit (20 psi)


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

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

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 .

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.?

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

1

2

3

4

5

1. 3DSearch2. 3DCompass3. 3DNavigation4. 3DHeads-Up5. Contextual

Buddy List

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

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

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


Y1

ConstraintBoundary

Y2

Initial Designfrom DOE


Outputs

Improve Design Performance

Optimization(Approximations)

Optimized Design

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


Y1

ConstraintBoundary

Y2


Outputs

Improve Design Quality

Design for Six Sigma

Robustness and Reliability Analysis and Optimization

Robust and ReliableDesign

% Unreliable% Reliable

Conclusion

SIMULIA / Abaqus / Engineous

- ein Update

Martin KssnerDassault Systemes Simulia GmbH

[email protected]

Documents

SIMULIA-Update-SPH CEL.pdf