Using Hyperstudy to pilot FEA-based designs of experiments on engine cooling module components

Altair Technology Conference June 2014 I 1 Property of Valeo. Duplication prohibited

Altair Technology Conference June 2014

Property of Valeo. Duplication prohibited

Using Hyperstudy to pilot FEA based Design of Experiment

Dr Benjamin THOMAS

Simulation & Vibration Expert


Summary

Introduction

Static stiffness scaling

Test-simulation DOE comparison

Sensitivity analysis

Conclusion


June 2014


Introduction 1


Valeo activities

Transmission Systems

Electrical Systems

Climate Control

Driving Assistance

Interior Controls

Wiper Systems

Lighting Systems

Thermal Powertrain

Thermal

Systems

Powertrain Systems

Comfort &

Driving

Assistance

Visibility

Systems


Team presentation

Valeo Thermal Systems, Thermal Powertrain FEA Simulation-Reliability Team

20 Persons (14 La Verrière-France , 6 Shangai-China)

Mechanical simulation and expertise for the worldwide network

Static, Dynamic, Thermomechanical, Rheology, Optimisation

Specification analysis/development

Thermal

Powertrain


Use of Design of Experiment in our team

New activity for our team

Parameters scaling

Introduce unknown or non-measurable properties

Test-simulation correlation

Compare response surface from test and simulation DOE


Understand the physics of our models


Process to link Hyperstudy and Abaqus

Template file

(Templex)

Simulation DOE

Abaqus input file

List of parameters

Text file Abaqus CAE or

Hypermesh

Hyperstudy Text Editor for

automatic translation

Hyperstudy generates the

DOE input files, launch runs

and post processings based

on a nominal run

The process is only based on text files manipulation


June 2014


Parameters Scaling 2


Position of the problem

Heat exchanger vibration simulation

Axial and radial rubber stiffnesses are unknown

2 Modes frequencies can be identified form test FRF


First attempt to scale rubbers properties

Data Test K=X N/mm K=100X N/mm

First mode

frequency 21 Hz 25Hz 79Hz

Trial/Error

x100 on axial stiffness x3 on the frequency

Find the parameters may be long and difficult!


Parameters scaling on Hyperstudy

Two main options:

Direct optimisation of the model:

Optimisation solver used

Parameters values obtained are exact values to use

In case of fast convergence, no data about the link between responses and factors

Design of experiment

Potentially more runs than using optimisation

Complete information about the sensitivity of the model

Enables to create a meta model

The DOE is used to get a better comprehension of the model


DOE based on our process

Parameters in the Templex are K1 and K2, 4 levels each

K1 and K2 must ensure the 2 first mode frequency to be in line with test results

The first mode frequency depends on both K1 and K2, but the second mode frequency depends only on K2

The response surfaces enables to scale the value to use thanks to surface approximation

K1 K1

K2 K2

F1 F2


June 2014


Test-simulation DOE comparison 3


Problem introduction

2 different ways to modelise cycled pressure on mechanical radiators tank

Test DOE based on the pressure and temperature variation is available

Tank + header alone: investigation on header stresses

Quick

Precise enough for a wide majority of case

Piece of the whole core

More complex and ressource consuming

Give information on tubes stresses


Test-simulation comparison

Location in the header Test results Simple model results Complex model results

Location 1

Location 2

Location 3

Location 4

DOE Tests Simple

Simulation DOE

ComplexSimulati

on DOE

Some values are well corelated on Location 1, but

improvement is needed. 2nd DOE leads to a better

tendancy and shows a way to improve stresses accuracy

even if location 1 is not a usual failure location


June 2014


Sensitivity Analysis 4



Aim

Identify the design factors contributing to the frequency shift of 2 modes of a fan to reduce acoustic emergencies using morphing operations

Examples of identified thickness

Several parameters identified to define designs for a DOE


Specific process

HYPERMESH: Mesh

HYPERMORPH: Shapes creation and export to Abaqus Format

HYPERSTUDY: DOE generation and results post processing

ABAQUS: Solver


The mesh retained is only 1/7th of the fan

Quicker runs

Mix tetra-hexa linear, the purpose in only to obtain a tendancy

Abaqus is able to understand the cyclic periodicity of the mesh, modes to analyse are complient with the periodicity hypothesis

Mesh


HYPERMORPH Morphing

The different shapes variations are stored as nodes perturbation

Hypermorph shapes are transformed in design variables and then exported as a text file in Abaqus format


Difficulties met & Results

Non morphable regions

Local material change used

Runs with cluster not so easy

Model still too big

Transfer of runs/outputs to be improved (Compute Manager?)

One of the mode is changing of position

Follow the mode is necessary, frequency must be corrected from the Abaqus dat file to be sure to work on the corresponding mode

The DOE enabled to identify significant impacts:

Up to 10% difference on frequencies with 0.3mm changes local thicknesses

Direct modification of the hub is possible to ensure desired behavior


June 2014


Conclusion 5


Conclusion

Interaction between Hyperstudy and external solver is very easy thanks to Templex

Strong benefits and interests of Hyperstudy piloted DOE compared to the investment

Quick parameters scaling

Quick sensitivity investigation

Automated simulation of test DOE

The main need on our side is a possibility to launch runs on cluster directly from Hyperstudy


Date post:	20-Jan-2015
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Using Hyperstudy to pilot FEA-based designs of experiments on engine cooling module components

Engineering