Lawrence Livermore National Laboratory


Lawrence Livermore is developing the capability to accelerate the certification of mission critical parts through the use of modeling and simulation. Predictive tools to derive the relationships between structure, processing, properties and performance - illustrated here by the well-known tetrahedron - are a key component of accelerated certification.

Simulating our way to faster part certification

The unique benefits of rapid build time and unique microstructural control offered by additive manufacturing processes cannot be fully realized with existing long certification times.

Lawrence Livermore National Laboratory is investing in a strategic initiative to address this challenge – the Accelerated Certification of Additively Manufactured Metals initiative.

The challenge is that manufacturers of additive manufacturing equipment cannot be expected to develop the processing and certification regimes for materials relevant to the mission of the National Nuclear Security Administration and the nuclear weapons complex. That equipment market is simply too small.

In industry, current estimates place the insertion of a single materials system into a complex design at tens of millions of dollars and 15 years. For nuclear weapons parts, the cost and time can be much greater, and these development cycles are no longer tolerable.

This strategic initiative will advance the field of additive manufacturing by:

  • Developing predictive process-structure-property relationships integrated with the AM process
  • Developing a thorough understanding of the basic physics of AM processes to capture the complexity in the multiple interacting physical phenomena
  • Developing sufficient understanding of processes to be able to prescribe processing conditions and achieve the desired properties in 1 or 2 attempts
  • Developing new sensors that can operate in build-chamber environments and can be used to feedback to the process

Realizing the benefits of rapid build time and microstructural control

The goal of this initiative is to develop predictive models that cover all time and length scales relevant to powder-bed additive manufacturing for metal parts. This internally funded research and development project builds on Lawrence Livermore's extensive expertise in materials science as well as its high-performance computational capability.

  • Develop process modeling and process optimization simulation and modeling capabilities.
  • Put in place a streamlined materials certification strategy to provide near-net-shape metal parts certified for use in critical applications at a significantly reduced cost, time, and waste.

We are employing modeling and simulation, process optimization, design of experiments, data mining, and uncertainty quantification as part of our AM materials strategy.

The initiative's strategy is based on an approach developed by the Institute for Computational and Mathematical Engineering (ICME) at Stanford University. This approach shifts the emphasis away from expensive manufacturing processes and integrated experiments to process aware modeling and simulation and exhaustive material characterization to understand the differences caused by new manufacturing methods. It is being combined with quantification of margins and uncertainties and expert peer review.

Initiative statement of purpose

We are an integrated, multidisciplinary team focused on developing the tools that will lead to acceleration of the certification of additively manufactured metal components through:

Physics based models Developing physics based models that relate microstructure, properties, and process (including post processing) to performance and are foundational to process control and certification.
Validating Experiments Providing validating experiments as prescribed by Design of Experiments; gaining scientific insights into simulations and experiments through data mining; and understanding how uncertainties in inputs influence the outputs by using UQ.
Integrated Sensing and Control Developing integrated in-process sensing, monitoring, and control technologies to ensure the end-processed material properties and component performance.
New Processes Developing new processes to improve quality, certifiability, and speed of additive manufacturing.

Wayne King


    Director, Accelerated Certification of Additively Manufactured Metals Initiative

    Wayne King


    Director, Accelerated Certification of Additively Manufactured Metals Initiative