nafems gothenburg 2005 veltri

NAFEMS SEMINAR

“Component & System Analysis Using Numerical Simula tion Techniques- FEA, CFD, MBS”| 23 – 24 November, 2005 | Gothenburg, Sweden

Virtual Product Development

Automated Durability Design of Crankshafts Based on MSC.Adams/Engine

Ing. Marco Veltri, Technical Consultant MSC.Software Ltd

NAFEMS Seminar “Component and System Analysis Using Numerical Simulation Techniques- FEA, CFD, MBS”

23 – 24 November, 2005 | Gothenburg, Sweden

Overview

• VPD, Virtual Product Development, applied to Crankshaft Design

• FEA – MBS and Fatigue tools• Problem size and missing link: the need for

automation

• Automated Process Flow• Assisted FEM, MBS and Fatigue simulation

analysis• The quest for automation: Managing Data vs.

producing data

Windows Explorer.lnk



• Design Tools: CAD modeling• FEA Pre&Post processing• Stress analysis tools• MBS “Loads generation tools”• VPD based fatigue analysis

-Historically each “station” implied separate departments, different software environments and unidirectional dialogue

-Modern trends command a tight integration and seamless flow, as in the case of component modal synthesis to abridge FEA to MBS

CAD FEA PRE-POST FEA STRESSES MBS FEA FATIGUE



Geometry and mesh

MSC.Patran

Mode shape analysis

MSC.Nastran

FEA PRE-POST FEA STRESSES

Solution path with Component modal synthesis



Component modal synthesis – Craig-Bampton Method

Partitioning the structure into internal and boundary DOFs:

Boundary DOFs (b)

Internal DOFs (i)

Boundary DOF’s are DOF’s of the nodes where the flexible body is connected to therest of the system, not necessarily geometry boundaries of the body. Boundary nodesNeed to be defined by user.

ffffffffff FuKuBuM =++ &&&

≅ ≅ ≅ ≅ Φq

Approximating the physical coordinates ui and ubwith their modal summation:

N

C

MC

bb

i

b

q

qoI

u

u

ΦΦ

{ }

=

= ii

b

NC

bb

i

bf u

uoI

u

uu

ΦΦ

≅≅≅≅

response to boundary displacements

fixed-boundary modal expansion



Geometry and mesh

MSC.Patran

Fatigue life calculation

Load histories

Mode shape analysis

System-level simulation

Mode shapes

Stress shapes

MSC.Nastran MSC.FatigueMSC.ADAMS

FEA PRE-POST FEA STRESSES MBS FEA FATIGUE

Strain Life Plot

605M30Sf': 857 b: -0.067 Ef': 0.636 c: -0.579

1E-3

1E-2

1E-1

Str

ain

Am

plit

ud

e

(M/M

)

1E0 1E1 1E2 1E3 1E4 1E5 1E6 1E7 1E8Life (Reversals)

0

1574.7 -750.4

808.70

4.8548

RangeuE

X-Axis

MeanuEY-Axis

DamageZ-Axis

DAMAGE HISTOGRAM DISTRIBUTIONMaximum height : 4.8548Z Units : %

Solution path with Component modal synthesis



Crankshaft design: Problem description and size

• Background• Assessment of Critical engine speeds through fatigue factor of

safety• Need for rapid prototyping and data retrieving• Using MSC.Nastran and MSC.Adams/Engine

• Basic requirements for Virtual Prototyping• Adequate Stress resolution • Inspect the complete operational speed range • Solve dynamic transient analysis with high angle reso lution

• Virtual Product Development solution• high FE mesh refinement with model of >500K nodes• Inspect the operational speed range with 100 rpm incre ments• Perform MBS modal transient analysis with FEA Flexibl e bodies• Modal stress recovery with 2 degree (or more) resolution angle



Auto Mesh Boundary nodes identification

Multi point Constraint (e.g. RBE3 and RBE2 in MSC.Nastran )

Manual, tedious, very error prone, risk of inconsistency: requires automation

CMS - modal reduction on large models

hotspot generation

Produces a results deck or several GB if all deformation and stress vectors are requested.

Requires focus

Engine run up analysis to cover all rpm range

Produces a Set of Modal Participation factors at each RPM (~50 sets)

Needs solution strategy and clever file handling

CAD FEA PRE-POST FEA STRESSES MBS FEA FATIGUE

Stress recovery and multiaxialFactor of safety for each engine speed (i.e. ~50 large fatigue jobs)

Screams for automation, efficient data handling and reporting

The required process for Crankshaft design would take s everal weeks to solve and would require immense system resource s!

Solution path to satisfy crankshaft design requirem ents:



the proposed efficient solution for Crankshaft desi gn:

• Preprocessing• Eliminate the manual, error prone tedious model

preparation• Reduce the model size by focusing on the assumed cri tical

areas

• Solving• Drive the MBS solver to maximize speed and data retriev al • Automate the subsequent multiple multiaxial fatigue

analyses

• Reporting• Automatically identify the most critical speed and relative

location



Craig-Bamptonmodes

Modal Stresses

For every modal vector, Stress concentrate around the Bearings

Stress analysis can conveniently be reduced to the “hot spots areas” to achieve great reduction of CPU time and disk space

A justification for a reduction to critical areas



A justification for a reduction to critical areas



FEM-Flex ModelsPart/ Meshes

Load Cases

Pre-Processing Reporting

AUTOMATION

SOL 103 +Nastran DMAP-Ishell

Individual subregion ofOp2 orthogonal stresses

Solving for Nastran-Adams-Fatigue

Modal data

Data Transfer

Proposed simulation workflow: no missing links!



Pre-Processing



Pre-Processing


Op2 orthogonal stresses for Individual hotspots

Solving for Nastran



Solving for Adams

• MSC.Adams is run in a single transient analysis spanni ng the whole operational rpm range using the following seque nce:• Settling time 5 to 10 Revolutions• Rpm_increase (by 100 rmp) 1 to 2 Revolutions• Output only 2 full revolutions at each measurement

• Parallel Processing implies simply distributing rpm rang es• CPU 1 from 1 to n_i Rpm• CPU 2 from n_i+1 to n_j Rpm



All Modal data is stored a single file !!

Engine Fatigue Toolkit• Input

• ADAMS results data• Hot spots• Orthogonal Stress

Vectors• Fast Modal Stress recovery

and Fatigue Analysis• High cycle fatigue• Multiaxial Dang Van

Criterion• Automatic Output

• Factor of Safety as a function of Rpm

Individual Op2 withOrthogonal modal stresses

Solving for Fatigue



Reporting

Engine Fatigue Toolkit• Each hotspot region

analyzed independently

• Factor of Safety as a function of Rpm is output interactively

• 6 curves above represent results from 200+multiaxia fatigue runs

• Full FEA Fatigue results information can optionally stored and be manually retrieved



FEM-Flex ModelsPart/ Meshes

Load Cases

Pre-Processing Reporting

AUTOMATION


Individual subregion ofOp2 orthogonal stresses

Solving for Nastran-Adams-Fatigue

Modal data

Data Transfer



Experiences

• Preprocessing time in both Nastran and Adams/engine has been virtually eliminated

• Solving time for Adams/Engine less then a day, with the option for linear improvement for parallel

• Fatigue solution time is a matter of minutes for each hotspot and rpm. The full engine operational range can be assesse d in 1 or 2days

• The whole design cycle for a basic engine variation c an be carried in 5 to 10 days (possibly 2 to 3 weeks for a redesig n)

• The quality or the results is not affected by the fas t process; actually it is benefiting from the added dimension in sensitivity• FEM element type (Solid Vs. surface, nodal Vs. elem ent)• Analysis variables such as Damping or modal truncat ion• Fatigue parameters to account for Stress gradients, hardening,

surface treatment, material condition etc..



In the quest for automation…

• Evident benefit of automation• Leverage commercial software• Identify risk factors fast and early• Remove errors and tedious repeatable tasks• Encapsulate knowledge

• NOT so evident benefits• Stochastic assessment• Solution Robustness• Data Efficiency

• handling, analysis and storing• Sharing, retrieving and transport across network



Fatigue Analysis vs. Fatigue Testing*Fatigue Analysis vs. Fatigue Testing*

Distribution of FE results

Distribution of test results

Single test result

Single FE result

Life results300 hours100 hours

any fatigue life specified must also be linked to a particular confidence level

*courtesy of Dr Neil Bishop of Random Loading Limited



Conclusions

• In complex problem such crankshaft design, a clever strategy supported by relatively simple programming can leverage well established off the shelf solutio ns to provide relevant enhancements, such as solution speed, results robustness and data handling

• Despite the seemingly unstoppable increase of solution power and system resources, engineering skills are still preferred to brute force

• Automation in solution processes and data handling is line with the vision and the need to manage data no t just producing it. This is becoming crucial as Terabytes of results are continuously produced and shared across deparments.



Thank you!

[email protected]

nafems gothenburg 2005 veltri

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