Manufacturing processes still hold many mysteries, even for the designers who plan them and the experts who carry them out. Researchers and quality control experts frequently use finite element modeling to forecast results or reevaluate past work; this involves assigning approximate values to unknowns over a defined number of points in a part being produced, then calculating formulas to resolve discrete problems, and finally coordinating the individual resolutions into a larger formula that can be applied to the entire component.
Researchers at LIFT are tackling a bigger mystery: how can FEM be applied in real-time to improve the results of forging production? Their efforts are going beyond FEM.
LIFT is the Lightweight Innovations for Tomorrow initiative, established in 2014 as a “manufacturing innovation institute” operated by the American Lightweight Materials Manufacturing Innovation Institute. It coordinates academic and institutional research with likely and/or available industrial partners, with specific development targets.
Two years ago, LIFT set out to develop “a localized physics-based visco-plastic finite element model” to predict mechanical deformation response, damage evolution mechanisms, and fatigue properties of forged Al-Li alloys. “We completed the first phase (of the research program), which was to develop the model for microstructure development and texture prediction in forging,” LIFT chief technology officer Alan Taub explained.
In the second phase, called “Forging and Processing of Al-Li for Improved Performance and Structural Life”, and in progress now, Taub and the project team are working to create a tool that engineers may use to model and predict mechanical responses of the material during forging. “Think of it as a model that gets ahead of the finite element model, and then feeds (data) into it,” he said.
Applying such a tool for aluminum-lithium engine component would mean a significant increase in engine efficiency and payloads, as well as significant reduction in cost and emissions, because of it would improve the reliability of those forgings in application.
The project team consists of United Technologies Research Center, Lockheed Martin, the University of Michigan, The Ohio State University, Case Western Reserve University and Southwest Research Institute.
According to Taub, extending the model’s function to be able to do ‘lightning’ predictions of microstructural changes taking place in the Al-Li component during forging “is a challenge because now we are going to be looking into crack growth and fatigue properties …”
Aluminum-lithium alloys are increasingly common in the design of commercial airframe parts, including for the Airbus A380 and A350 and the Boeing 787 Dreamliner. The appeal is the alloy’s low structural mass but high strength and strain resistance, factors which also make aluminum-lithium difficult to form.
LIFT started the research as part of a broad mission to improve manufacturers’ ability to produce lightweight materials for transportation, to determine the right material properties for specific component designs, and to optimize production methods to maintain those objectives.
“It’s really part of the broader Integrated Computational Materials Engineering (ICME) global initiative,” Taub said of the model development. “By optimizing the process to produce the right microstructure locally, we can make a more efficient design, and therefore lighten the weight (of the forged component.)”
The current work involves developing models for the metallurgical transformation of Al-Li during forging, and then translating that information to understand the mechanical property changes at a local level. “I think what distinguishes this work is that it went from fundamental data – what was sometimes referred to as ‘atoms to autos’ or ‘atoms to aircraft’ — and gets back to first principles of crystal plasticity, in order not just to model the microstructure but also the texture development (of the material),” Taub commented. “And that’s really the remarkable development out of the first phase of the project, which is that we can not only predict grain structure but we can predict texture.
“We’re at the stage now where the tools are being developed around single-use cases,” he said. But, once the model is demonstrated successful for forging aluminum-lithium alloys it may be applied to other materials, and to other forming processes.
“Right now the goal of the ICME models is to form the bridge between the manufacturing process model and the design model, during the product development process. It clearly will also have application in the control strategy that follows,” Taub said.
Still, there is no mystery about the importance of the results to date: Later this month, Lightweight Innovations for Tomorrow will be recognized by TechConnect Defense with a 2018 Innovation Award for the ongoing research into improved modeling of aluminum-lithium forgings.
