ICME approach to Additive Manufacturing Modeling and … · • DARPA Open Manufacturing “Rapid Low Cost Additive ... •ICME-informed process optimization, combined with leading

CHiMaD/SRG31

32nd Annual Meeting

David SnyderSenior Materials Engineer

QuesTek Innovations LLC

March 22, 2016

ICME approach to Additive Manufacturing –

Modeling and Alloy Design

QuesTek Innovations—SRG 201622 March 2016

• Increasing interest in the development of new alloys specifically designed for AM

• Alloy producers, OEMs, government

• Adaptation of traditional wrought/cast alloys to AM processing presents limitations

• AM design considerations:

• Complex thermal histories− Rapid solidification

− Intense residual stresses

− Non-equilibrium microstructures

• Impurity tolerance

• Geometry-dependent behavior (reliability)

• Novel alloy design strategies

QuesTek sees increasing interest in the design and development of improved alloys for additive manufacturing

Motivation


• DARPA Open Manufacturing “Rapid Low Cost Additive Manufacturing” (Ni superalloys; Honeywell)

• ONR Phase II SBIR “Computational Design of Aluminum Alloys for Use in Additive Manufacturing”

• NAVAIR Phase I SBIR “Development of 7050 T-74 Aluminum Alloy Alternative for use in Additive Manufacturing (AM)

Systems”

• Ti alloys for additive manufacturing (Sciaky EBAM)

• Army Phase I SBIR “Application of ICME to Optimize Processing of State-of-the-art Gear Steels in Additive

Manufacturing”

• AFRL MAI (Honeywell) “ICME Development for Additive Manufactured Aerospace Components”

• Commercial projects and proposals, AM committee participations

Current QuesTek AM project highlights


Aluminum Alloy Development for Additive Manufacturing

ONR Phase II SBIRAluminum AM for Helicopter Gearbox Housings

NAVAIR Phase I SBIRHigh-strength Aluminum AM for Aircraft Structures


Project Goals

• Current Al AM alloys are low

performance casting alloys (AlSi12,

AlSi10Mg)

• AM of high-strength Al (e.g. 6061,

7050) limited by Hot Tearing

– Driven by high residual stress, sub-

optimal solidification behavior

• Program Goal: High-strength,

precipitation hardenable Al

optimized for AM

– Structural Alloys

– High-temperature Alloys

Comparison of AlSi10Mg and Al-6061 Processed Through DMLS

B. Fulcher et.al, 2014 SFF Symposium proceedings

Hot tearing in 6061 processed by DMLS

X-Y plane

X-Z plane


Project Goals

Critical trade-off between Precipitate Strengthening and AM Processability


Design for Hot Tearing

• Hot tearing susceptibility is (partly) driven by an alloy’s capacity for interdendritic liquid feeding during the final stages of solidification

• Cracking Susceptibility Coefficient (CSC) defined to forecast crack susceptibility from solidification path

CSC correlates well with known castability / DMLS processability

Example non-equilibrium solidification simulation

Decreasing

processability


Design for Strength

• Thermodynamic calculations inform phase stability as a function of composition

for tailored microstructures and control of processing windows

• Mechanistic strength models utilized to inform composition and processing route to achieve property goals

Mechanistic strength modeling

Quench Sensitivity modeling


• 7xxx series aluminum for additive manufacturing:– Incorporate novel non-equilibrium Zn-based eutectic for hot cracking resistance

– Computational optimization between eutectic content (processability) and η’-phase strengthening (performance)

Region of combined strength + hot

tearing resistance

Computational Optimization between performance and processing

Integration of material models to visualize trade-off between design metrics

Example Design Integration

iCMDTM


Feasibility Study: Bead-on-plate

• Experimental study to assess weld crack

sensitivity ahead of atomization and DMLS

• 3 concepts designed for hot tearing and:

– Strength (7000-concept)

– High temperature (2000-concept)

– Corrosion resistance (PH5000-concept)

• Successful elimination of hot cracking,

coupled with high precipitation

hardening response

On par with baseline 7050-T74


• Phase I feasibility demonstration– Inert gas atomization, 100-lb scale

• Preliminary DMLS process optimization at Stratasys Mfg (Belton, TX)

– EOS M280

– DoE approach to establish effects of process variables on density, microstructure

• Demonstration of high precipitate strengthening with DMLS processability

• In process: 2nd generation prototyping

Prototype DMLS Evaluations


Ongoing Activities

• Currently in Phase II (2 year program)

• Scaled-up powder production of multiple concept

alloys (>400 lb)– LPW Technology, Inc. (Pittsburgh, PA)

• Extended DMLS evaluations and property

demonstration– Stratasys Direct Manufacturing (Belton, TX)

• Component-level builds


Rapid Qualification of DMLS-718+ Ni Superalloy


• QuesTek’s castable Ti alloy has been processed by the EBAM AM process (Sciaky)

• “ICME-designed” to have a refined microstructure on cooling (ideal for AM)

• Enhanced strength + ductility over cast/EBAM Ti-64

AM of QuesTek castable titanium alloys


AM of high-performance gear steel Ferrium C64

Powder Production

Deposition Optimization

Microstructural Evaluation

Coupon Deposition

Property Validation

• Army need for high-performance AM gear material for use in rapid design/prototype efforts

• Best-in-class Ferrium C64 adapted for AM

• ICME-informed process optimization, combined with leading AM industry knowledge and OEM support

• Evaluate performance and potential for fatigue-driven applications


• The complexity of AM processing makes it an ideal candidate for ICME methodologies

• Additive manufacturing is unique from cast and wrought processes – alloys should be uniquely customized as well

• Enhanced AM processability and achievable performance

• ICME modeling is being applied to forecast design allowables for parts produced by AM

• More efficient experimentation; Accelerated specification development; Improved confidence

Summary

Documents

ICME approach to Additive Manufacturing Modeling and … · • DARPA Open Manufacturing “Rapid Low Cost Additive ... •ICME-informed process optimization, combined with leading