Lawrence Livermore is working with the LIFT consortium to develop methods for predicting the behavior of new materials.

Multijunctions, elements formed in the crystalline structure of materials when three or more dislocations collide, help to strengthen metals.

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Reducing Development Time of New Lightweight Materials

Computers Speed Development

Strong, lightweight materials development

for automobiles and aircraft creates

significant fuel savings by moving less

mass from one point to another. It often

takes years to develop and characterize

new materials. Typically, researchers

hypothesize new material constituents,

manufacture the material, and then

subject the new material to a series

of tests to determine its properties.

Researchers at Lawrence Livermore

National Laboratory (LLNL) help to speed

up this process using new computational

techniques and supercomputers to

predict—in advance of fabrication—the

properties of new candidate materials.

Using computational methods, materials

experts can perform “virtual” experiments

on several variations of the constituents

and design a material that meets desired

performance specifications.

An industrial consortium called Lightweight

Innovation for Tomorrow (LIFT), which

includes several major aerospace

companies, was interested in replacing

heavy titanium alloys in aircraft engine

turbine blades with a new lighter alloy.

They first selected aluminum as a light

material, but aluminum did not exhibit

the strength of titanium. LIFT realized

by adding the light element lithium to

aluminum as precipitates that they

would strengthen the resulting alloy. The

consortium decided to computationally

test this idea as a faster way to vet

the concept. In a project funded by the

Department of Energy High Performance

Computing for Manufacturing (HPC4Mfg)

Program, researchers at LLNL worked with

the LIFT consortium to computationally

predict the strength of the aluminum-

lithium alloy as a function of the

percentage of lithium precipitates in the

alloy.

Predicting Alloy Strength

Engineers typically determine if a part

such as a turbine fan blade can survive

the stresses incurred during operation by

simulating the fan blade’s response to

stress using a computational technique

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This document was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or Lawrence Livermore National Security, LLC. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or Lawrence Livermore National Security, LLC, and shall not be used for advertising or product endorsement purposes.

This chart shows the stress/strain response of aluminum–lithium alloys as a function of the percentage of lithium precipitates in the aluminum matrix.

known as the finite element method.

In particular, engineers want to know

if the material deforms under stress.

At each point in the computational

domain, a constitutive material model

can be defined to accurately represent

the alloy’s response to external loading

conditions. The stress/strain response

of the material can be predicted based

on the inherent dislocation density of the

material and movement of dislocations

through the material as it plastically

deforms under loads. Impurities or

precipitates in the lattice can inhibit

the motion of these dislocation lines

and thus strengthen the base material.

Computational researchers at LLNL built

a model to accurately predict movement

of lines of dislocations through the

material and the interactions between

dislocation defects and precipitates

present in the alloy.

In that project, researchers used the

lightweight metal aluminum as the

base metal, and the lightweight metal

lithium as the precipitate. Through

the model results, the team could

visualize the lines of dislocations

moving through the material, around

and through the precipitates, and

inhibit further dislocation movement

as the plastic deformation increased.

In this way, stress-strain curves are

generated as a function of percentage

of lithium— predicting, for example, that

the yield strength of a five percent lithium-

aluminum alloy exhibits a three times

higher yield strength than a one percent

lithium-aluminum alloy. Using analyses

such as these, LIFT aerospace engineers

can determine if the new material will

meet the strength specifications for the

parts being considered for replacement.

Cost-Effective Replacement for Titanium Parts

Ultimately it is hoped that the new alloy

will be a replacement for the more

expensive and heavier titanium hubs of

turbine blades in jet engines. Over 13

million gallons ($26M) could be saved per

year industry-wide using the new material

for turbine blades in aircraft engines.

Researchers are continuing to expand

their predictive capabilities to better

contribute to new future materials. Later

work will consider different alloy systems

and polycrystalline materials.

How to Work With Us

For more information, visit hpc4mfg.org or

contact us at hpc4mfg@llnl.gov.

High Performance Computing for Manufacturing Labs

ENERGYU.S. DEPARTMENT OF