Webinar optiSLang & ANSYS Workbench

37 Pages·2016·2.16 MB·English

Webinar
optiSLang & ANSYS Workbench
Dynardo GmbH
1
© DynardoGmbH
1. Introduction
2. Process Integration
and variation studies
6. Signal
Processing
3. optiSLang
inside ANSYS
5. ANSYS Mechanical
APDL in optiSLang
4. ANSYS Workbench
node in optiSLang
Webinar optiSLang and ANSYS Workbench 2
© DynardoGmbH
Introduction
Webinar optiSLang and ANSYS Workbench 3
© DynardoGmbH
Excellence of optiSLang
• is an general purpose tool for variation analysis
using CAE-based design sets (and/or data sets) for
the purpose of
• sensitivity analysis
• design/data exploration
• calibration of virtual models to tests
• optimization of product performance
• quantification of product robustness and product reliability
• Robust Design Optimization (RDO) and Design for Six
Sigma (DFSS)
serves arbitrary CAX tools with support of process
integration, process automation and workflow
generation
Webinar optiSLang and ANSYS Workbench 4
© DynardoGmbH
Robust Design Optimization
Optimization Robust Design
Variance-Based
Sensitivity Analysis
Robustness Evaluation
Single- & Multi-Objective
Probability-Based
(Pareto) Optimization
Robustness Evaluation
Start
CAE process
(FEM, CFD, MBD, Excel, Matlab, etc.)
Webinar optiSLang and ANSYS Workbench 5
© DynardoGmbH
optiSLang: Graphical User Interface
Build, Run and Analyze your flow using
• Wizards
• Comfortable Drag&Drop
• Dialogs and Tables
• Postprocessing
Webinar optiSLang and ANSYS Workbench 6
© DynardoGmbH
Process Integration
and variation studies
Webinar optiSLang and ANSYS Workbench 7
© DynardoGmbH
Process Integration
Parametric model as base for
• User defined optimization (design) space
• Naturally given robustness (random) space
Design variables
Entities that define the
design space
Response variables
The CAE process Outputs from the
Generates the system
results according
Scattering variables
to the inputs
Entities that define the
robustness space
Webinar optiSLang and ANSYS Workbench 8
© DynardoGmbH
optiSLang Integrations
Direct integrations
ANSYS Workbench

Matlab

Excel

Python

SimulationX

Supported connections
Ansys APDL

Abaqus

Adams

AMESim

…

Arbitary connection of
ASCII file based solvers
Webinar optiSLang and ANSYS Workbench 9
© DynardoGmbH
Metamodel of Optimal Prognosis (MOP)
• A fully automatic workflow identifies the subspace of important parameter
with the best possible meta-model (MOP) of every response variable
resulting in the best possible forecast quality towards result variation
• Include multi-dimensional nonlinear dependencies with automatic
identification + ranking of important input variables
MOP Solves 3 Important Tasks:
1 Best Input Variable Subspace
st
2 Best Meta-model
nd
3 Estimation of Prediction Quality
rd
DoE MOP
Solver
Webinar optiSLang and ANSYS Workbench 10