Robust Design and Optimization using modeFRONTIER 2011 Yael Kaldor.pdf · From Design to...

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Proprietary of Rafael - Armament Development Authority Ltd

ADVANCED DEFENCESYSTEMS Ltd.

8 December 2011RAF#41035011

Robust Design and Optimization using modeFRONTIER

Missiles & NCW Division

R & D and Engineering

Directorate

Yael K. - Rafael

Incose IL 2011 , Herzliya 8-9 March 2011

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Good (and getting better) design capabilities using various CAD software

High computation power : Strong computers / Computer clusters / Parallel computing

Ability to model large complicated structures without the need of compromise in meshing

Strong simulation and analysis capability and good correlation to actual measured results

Design – NowadaysADVANCED DEFENCESYSTEMS Ltd.



Directorate

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Our desire is to improve manufacturing capability of the product by improving its’ robustness:

From Design to Manufacturing ADVANCED DEFENCESYSTEMS Ltd.



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Sensitivity analysis and verification of the compliance to spec – during the design stage

Selection in advance of the robust design out of the various available designs –Design For Manufacturing

Multi-Disciplinary optimization

Optimal solution

RobustOptimal solution

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Input Variables:The varaibles which define the evaluated model

Black Box:Evaluates the Output as a function of the Input Variables

Output Variables:A result of the calculation in the Black Box

The Idea Behind modeFRONTIER

8 December 2011



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Interfaces at a top level to various soft wares:

The Idea Behind modeFRONTIER ADVANCED DEFENCESYSTEMS Ltd.



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CST

Excell

Matlab

Mathcad

Pro-E

Solidworks

Ansys

CATIA

It’s possible to create an interface to any software Supports Various (20 ) DOE

schemes and 20 Optimization Methods Built – in Optimization Wizard

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Defining the WorkflowADVANCED DEFENCESYSTEMS Ltd.



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Input Variables

Application Node

Output Variables

Design Objective

Design Constraint

Optimization and DOEscheme

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The design SpaceADVANCED DEFENCESYSTEMS Ltd.



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This is the post processing windowOptimization results are presented and updated in Real Time

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mF - Design SpacePost Processing Charts

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Final R_loss Target: MinimizeConstraint: - 9 dB max

Bubble ChartBubble Chart

mF - Design SpacePost Processing

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Pareto Frontier

Obj

ectiv

e1

Objective2

Scatter ChartScatter Chart




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Parallel CoordinateParallel CoordinateChartChart




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Robust Design and Optimization of Antennas using CST and mF

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ElectromagneticCAD Software




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H

L

hp

Φ r

Input port Dielectric Slot

CST Model CST Model –– Antenna Antenna sectionsection

Optimization ParametersOptimization Parameters

Matching over the full frequency range was nearly impossible due to dimension constraints and coupling from the platform

Simulated Performance was initially very poor

Initially the parameters which mostly effect the matching performance were identified.

The parameterized CST model

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modeFRONTIER - Optimization WorkflowADVANCED DEFENCESYSTEMS Ltd.



Directorate

R_loss_f_low

R_loss_f_cen

R_loss_f_high

Output Variables

Minimize(maximum) Maximum < -10 dB R.Loss

Design Objective Design Constraint

slot_length

stub

r_stub

pin_dist

partstub

slot_h

Input Variables

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Spec

FhighFlow Fcenter

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FhighFlow Fcenter

Design Goal

Spec

Design Goal

Before Optimization

Electrical Matching Performance

After Optimization




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Parallel CoordinateChart

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Bubble Chart

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The various charts depict the full design space, the history of the optimization an its progress towards the optimal solution.

The various post processing charts help us understand the physics of the problem and allows statistical analysis of the results.

In this sense mF is a valuable decision making tool.




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modeFRONTIER - Design Spacepost processing charts

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Option 1 - Sensitivity Analysis

for selected optimized solutions – sensitivity check as a part of the design process during the simulation stage

choose from various optimized solutions the less sensitive solution

Option 2 – Design for Manufacturing

Optimize for the MEAN and STD DEV of the required solution – (Design for 6 SIGMA)

Option 3 – Multidisciplinary Optimization

Optimize for several disciplines simultaneously

Design for Robustness




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Robust Design and Optimization using modeFRONTIER 2011 Yael Kaldor.pdf · From Design to...

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