Post on 26-Oct-2015
description
1
Webinar
optiSLang 4 & ANSYS Workbench
Dynardo GmbH
2Webinar optiSLang 4 and ANSYS Workbench
Excellence of optiSLang
• optiSLang is an algorithmic toolbox for
sensitivity analysis, optimization,
robustness evaluation, reliability analysis
and robust design optimization (RDO)
• optiSLang is the commercial tool that has
completed the necessary functionality of
stochastic analysis to run real world
industrial applications in CAE-based
robust design optimizations
• optiSLang offers the beginner and
expert users an easy and reliable
application by means of predefined
workflows, algorithmic wizards and
robust default settings
3Webinar optiSLang 4 and ANSYS Workbench
Start
CAE process (FEM, CFD, MBD, Excel, Matlab, etc.)
Robust Design Optimization
Optimization
Sensitivity Study
Single & Multi objective (Pareto) optimization
Robust Design
Variance based Robustness Evaluation
Probability based Robustness Evaluation, (Reliability analysis)
4Webinar optiSLang 4 and ANSYS Workbench
Graphical User Interface
5Webinar optiSLang 4 and ANSYS Workbench
optiSLang 4: Graphical User Interface
Build, Run and Analyze your flow using• Wizards• Comfortable Drag&Drop• Dialogs and Tables• Postprocessing
6Webinar optiSLang 4 and ANSYS Workbench
Nodes
• Input
• Process / Properties
• Output
Connections
• Data flow
• Triggering
Graphical Programming
7Webinar optiSLang 4 and ANSYS Workbench
Process Integration
8Webinar optiSLang 4 and ANSYS Workbench
Process Integration
Parametric model as base for
• User defined optimization (design) space
• Naturally given robustness (random) space
Design variablesEntities that define the design space
Response variablesOutputs from the system
The CAE processGenerates the results according to the inputs
Scattering variablesEntities that define the robustness space
9Webinar optiSLang 4 and ANSYS Workbench
Signals in optiSLang
• Signals are vector outputs having an abscissa (e.g. time axis)
and several output channels (e.g. displacements, velocities)
• Comprehensive library of signal functions enables the user to extract
local and statistical quantities and to analyze differences between
several signal channels e.g. for calibration tasks
• Automatic mapping of non-consistent abscissa discretizations for the
signals of each design and of the reference curves
• Direct access to signal plots in the optiSLang postprocessing and
interactive connection to the statistic/optimization postprocessing
10Webinar optiSLang 4 and ANSYS Workbench
optiSLang 4 Integrations
Direct integrations� Matlab� Excel� Python� SimulationX� Ansys Workbench
Supported connections� Ansys� Abaqus� Adams� …
Arbitary connection ofASCII file based solvers
11Webinar optiSLang 4 and ANSYS Workbench
Full integration of optiSLang in Ansys Workbench
• optiSLang modules Sensitivity, Optimization and
Robustness are directly available in ANSYS Workbench
12Webinar optiSLang 4 and ANSYS Workbench
The Workbench Integration
• The workbench node directly connects to
the workbench project and gets the inputs
and outputs from the parameter set
13Webinar optiSLang 4 and ANSYS Workbench
© Dynardo GmbH
Sensitivity Analysis
14Webinar optiSLang 4 and ANSYS Workbench
© Dynardo GmbH
Scanning the Design Space
Inputs Design of Experiments Solver evaluation Outputs
• Uniform distribution of inputs is represented by Latin Hypercube Sampling
• Minimum number of samples should represent statistical properties, cover the input space optimally and avoid clustering
• For each design all responses are calculated
15Webinar optiSLang 4 and ANSYS Workbench
Metamodel of Optimal Prognosis (MOP)
• Approximation of solver output by fast surrogate model
• Reduction of input space to get best compromise between available
information (samples) and model representation (number of inputs)
• Determination of optimal approximation model
• Assessment of approximation quality
• Evaluation of variable sensitivities
© Dynardo GmbH
16Webinar optiSLang 4 and ANSYS Workbench
© Dynardo GmbH
Multi-Disciplinary Optimization
17Webinar optiSLang 4 and ANSYS Workbench
© Dynardo GmbH
Multidisciplinary Optimization with optiSLang
CAD and CAE Parameter definition
Sensitivity study – identify the most important parameters and check variation/COD of response values
minimize
Define optimization goal and optimize
Validate optimized design in CAE and CAD
18Webinar optiSLang 4 and ANSYS Workbench
© Dynardo GmbH
optiSLang Optimization Algorithms
Gradient-based Methods
• Most efficient method if gradients are accurate enough
• Consider its restrictions like local optima, only continuous variablesand noise
Adaptive Response Surface Method
• Attractive method for a small set of continuous variables (<20)
• Adaptive RSM with default settings is the method of choice
Nature inspired Optimization
• GA/EA/PSO imitate mechanisms of nature to improve individuals
• Method of choice if gradient or ARSM fails
• Very robust against numerical noise, non-linearity, number of variables,…
Start
19Webinar optiSLang 4 and ANSYS Workbench
Pareto Optimization
• Find a set of solutions close to the Pareto-optimal solutions
• Find solutions which are diverse enough to represent the whole front
Strength Pareto Evolutionary Algorithm
• Elitism is applied by using an archive
of non-dominated individuals
• Fitness assignment is based on the
dominance criterion
• Preservation of population diversity
is realized by density estimation
• Suitable start population significantly
improves convergence
© Dynardo GmbH
20Webinar optiSLang 4 and ANSYS Workbench
Decision Tree for Optimizer Selection
• optiSLang automatically suggests an optimizer depending on the
parameter properties, the defined criteria and user specified settings
© Dynardo GmbH
21Webinar optiSLang 4 and ANSYS Workbench
© Dynardo GmbH
Robustness Analysis
22Webinar optiSLang 4 and ANSYS Workbench
© Dynardo GmbH© Dynardo GmbH
Variance based Robustness Analysis
1) Define the robustness space using scatter range, distribution and correlation
2) Scan the robustness space by producing and evaluating ndesigns
3) Check the variation 4) Check the
explainability of the model
5) Identify the most important scattering variables
23Webinar optiSLang 4 and ANSYS Workbench
Training Program
24Webinar optiSLang 4 and ANSYS Workbench
© Dynardo GmbH
Training
optiSLang 4 Basics
• 3 day introduction to process integration (ASCII, Matlab, Excel, Python),
sensitivity, optimization, calibration and robustness analysis
optiSLang inside ANSYS Workbench
• 2 day introduction seminar to parameterization in ANSYS Workbench
and sensitivity analysis and optimization via optiSLang inside ANSYS WB
optiSLang 4 and ANSYS Workbench
• 1 day introduction to the integration of ANSYS Workbench projects in a
optiSLang 4 solver chain, parameterization of signals via APDL output
optiSLang 4 Update
• 1 day update seminar introducing process integration and automation
with optiSLang 4 (for optiSLang 3 users)
25Webinar optiSLang 4 and ANSYS Workbench
Examples
26Webinar optiSLang 4 and ANSYS Workbench
Optimization of a Hook
How to change the hook, so that
• The v.-Mises stress will not exceed 300MPa,
• The mass will be as minimal as possible and
• Certain geometry parameters will be in predefined bounds?
27Webinar optiSLang 4 and ANSYS Workbench
DS_Angle (120-150°)
DS_Thickness (15-25 mm)
DS_LowerRadius (45-55 mm)
DS_Depth (15-25 mm)
Optimization of a Hook
Design parameters (at DesignModeler)
28Webinar optiSLang 4 and ANSYS Workbench
Solver: ANSYS® Mechanical
• Open the ready to use Workbench project hook.wbpz
• In ANSYS Workbench ANSYS Mechanical is used as solver
1.
29Webinar optiSLang 4 and ANSYS Workbench
Results of the Sensitivity Analysis
• The approximation quality is excellent for both output variables
• The influence of the angle and the lower radius is relatively small
30Webinar optiSLang 4 and ANSYS Workbench
Initial vs. Optimal Design
Initial Design Optimal Design
Mass = 752g Mass = 613g
Equivalent Stress = 460MPa Equivalent Stress = 299MPa
31Webinar optiSLang 4 and ANSYS Workbench
Damped Oscillator
• Single degree-of-freedom system
excited with initial kinetic energy
• Equation of motion of free vibration:
• Un-damped and damped eigen-frequency
• Time-dependent displacement function
32Webinar optiSLang 4 and ANSYS Workbench
• Optimization goal: Minimize maximum
amplitude after 5s free vibration:
• Restricted damped eigen-frequency
as optimization constraint:
• Mass and stiffness as optimization
variables, damping ratio and
kinetic energy as constant
The Optimization Task
33Webinar optiSLang 4 and ANSYS Workbench
• Robustness evaluation at
the deterministic optimum
• Mass m, damping ratio D, stiffness k and initial kinetic energy as
normally distributed random variables
Robustness Analysis
34Webinar optiSLang 4 and ANSYS Workbench
Solver: MS Excel
• Open the ready to use Workbench project via the start menu:
� All Programs/optiSLang/Ansys Workbench/Examples/oscillator.wbpz
• In ANSYS Workbench Microsoft Office Excel is used as a solver
35Webinar optiSLang 4 and ANSYS Workbench
Cantilever Beam
• Finite Element model in ANSYS Workbench
• Elastic material behavior
• Cantilever beam is deformed by a predefined external displacement
• Reaction forces at deformed beam end are monitored depending on
deformation and written to text output file via APDL
36Webinar optiSLang 4 and ANSYS Workbench
Problem Definition
• Identification of the geometry
parameters that a given
reference force displacement
function is achieved
• Parameter bounds:
Thickness 0.8 – 1.2 mm
Radius 32.0 – 37.0 mm
Depth 2.5 – 3.5 mm
Height 5.0 – 15.0 mm
• Objective function is the sum of squared errors between the reference
and the calculated force values
37Webinar optiSLang 4 and ANSYS Workbench
The Solver Chain
• The solver chain contains the workbench node and an additional text
output node to read the APDL output file
• The reference is obtained by another text output node
38Webinar optiSLang 4 and ANSYS Workbench
Results of the Sensitivity Analysis
39Webinar optiSLang 4 and ANSYS Workbench
Results of the Optimization