leveraging geometric shape complexity, in optimal design for additive manufacturing

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Copyright © 2015 by Optimal Structures, LLC LEVERAGING GEOMETRIC SHAPE COMPLEXITY IN OPTIMAL DESIGN FOR ADDITIVE MANUFACTURING Yobani Martinez Robert Taylor Optimal Structures 2015 ATCx Conference Houston, TX October 8, 2015

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Page 1: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Copyright © 2015 by Optimal Structures, LLC

LEVERAGING GEOMETRIC SHAPE

COMPLEXITY IN OPTIMAL DESIGN FOR

ADDITIVE MANUFACTURING

Yobani Martinez

Robert Taylor

Optimal Structures

2015 ATCx Conference

Houston, TX

October 8, 2015

Page 2: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Introduction

• Objective: Use Solid Thinking Inspire to develop

structural design concepts to leverage additive

manufacturing capabilities

• DFAM Discussion

• Case studies

• Hinge

• Upright

• UAV

• Observations

Page 3: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Design for Additive Manufacture

• AM enables

• Low volume (lot size of one)

• Easier design change integration (prototyping, customization)

• Piece part reductions (component combination)

• Complexity

• Geometric shape

• Hierarchical—shape complexity across multiple size scales

• Material—pointwise, layerwise

• Functional—assemblies, mechanisms

• Product performance improvement (design to match physics)

• Multi-functionality (structural and thermal and fluid and…)

Page 4: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Design for Additive Manufacture

• Increased geometric shape complexity can improve

structural performance (design to match physics)

• Capability to fabricate layer unrelated to layer shape

• Machining, molding operations limited by tool accessibility, mold

separation requirements

• Extreme complexity possible—mesostructures

• Lattice structures

• Load efficiency interaction

• Bending vs. Torsion

• Focus of current study

Page 5: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Aircraft Door Hinge Study

• Compare optimized configuration for conventional and additive manufacturing

• Requirements • Loads

• Bending

• Side loadtorsion

• Constraints • Displacement

• Stress

• Stability

• Topology Optimization • Package Space (design, nondesign)

• Objective: maximize stiffness

• Constraint: volume fraction • Conventional Manufacture (draw direction) vs Additive

Manufacture (no draw direction)

Page 6: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Aircraft Door Hinge Study

40% Volume Fraction 30% Volume Fraction

With draw direction—conventional manufacturing

Without hole

With hole

Page 7: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Aircraft Door Hinge Study

40% Volume Fraction 30% Volume Fraction

Without draw direction—additive manufacturing

Page 8: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Aircraft Door Hinge Study

Surface Definition using Evolve • MeshNURBS to remove data noise

• Complex surfaces—lofts, blends

Page 9: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

New CAD Part

Conventional Manufacturing Process

• With draw direction constraint

• Total mass 6.8 lbs

Aircraft Door Hinge Study

Page 10: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Additive Manufacturing Process

• Without draw direction constraint

• Total mass 4.6 lbs (-33%)

Aircraft Door Hinge Study

Page 11: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Formula Race Car Upright Study

• Compare optimized configuration for conventional and additive manufacturing

• Requirements • Loads

• Hard turn

• x-bending

• y-torsion

• Braking

• Z-bending

• Constraints

• Displacement

• Stress

• Stability

Weight 2.68 lbs

Space 12 x 3 x 5.5 in.

Aluminum 6061

Page 12: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Formula Race Car Upright Study

• Compare optimized

configuration for

conventional and additive

manufacturing

• Topology Optimization

• Package Space (Design,

Nondesign)

• Objective: maximize stiffness

• Constraint: volume fraction

• Conventional Manufacture (draw

direction) vs Additive

Manufacture (no draw direction)

Page 13: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

With draw direction—conventional manufacturing

Formula Race Car Upright Study

Volume Fraction 25% Volume Fraction 35% Volume Fraction 45%

Page 14: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Formula Race Car Upright Study

Without draw direction—additive manufacturing

Volume Fraction 25% Volume Fraction 30%

Page 15: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Min Value .9’’ Min Value .5’’ Min Value .7’’ Min Value .3’’

Formula Race Car Upright Study

Without draw direction—additive manufacturing

• 30 % volume fraction

• Max is double the min

Page 16: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Formula Race Car Upright Study

• Surface modeling in Evolve • Separate design,

non-design regions

• Start with polymesh cube

• Move and deform to match topology results

• Nurbify

Page 17: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Formula Race Car Upright Study

• Surface

modeling in

Evolve

• Import non-

design regions

• Trim, blend,

edit to get final

model

Page 18: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Draw

constraint

Draw

constraint

Formula Race Car Upright Study

No draw

constraint

Ongoing Work

• Size, shape

optimization

Automotive Upright Optimization

for Additive Manufacture

Page 19: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

UAV Design Study

• Rapidly develop fuselage internal

structural configuration concept for

FDM-printed aircraft

• Thin wall structure

• Determine internal stiffening configuration

• 5 load conditions—bending about 2 axes

Wing

bending

Wing

torsion

Pitch Down

Vector

Pitch Up

Vector

Nose

landing

Page 20: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

UAV Design Study

• Configuration

• Topology interpretation for thin

wall structure not always intuitive

• No buckling effects considered

• Sizing challenge

• Hollow members with infill

patterns

• Strength

• Stiffness

• Stability

Page 21: Leveraging Geometric Shape Complexity, in Optimal Design for Additive Manufacturing

Observations

• Inspire greatly accelerates topology optimization process

for supported modeling capabilities

• Excellent start, not final design

• Additive manufacturing enables complexity

• Geometric shape can closely match physics (load efficiency

interaction)—weight reduction

• Topology-optimized configuration requires CAD expertise—Evolve

can help

• Increases complexity of downstream shape and sizing optimization

needed to satisfy strength, stiffness, and stability criteria