4th World Congress on Integrated Computational Materials Engineering (ICME 2017): ICME Success Stories and Applications - I
Program Organizers: Paul Mason, Thermo-Calc Software Inc.; Michele Manuel, University of Florida; Alejandro Strachan, Purdue University; Ryan Glamm, Boeing Research and Technology; Georg J. Schmitz, Micress/Aachen; Amarendra Singh, IIT Kanpur; Charles Fisher, Naval Surface Warfare Center
Wednesday 10:30 AM
May 24, 2017
Room: Salon IV
Location: Ann Arbor Marriott Ypsilanti at Eagle Crest
Ferrium M54 – ICME Development from Genome to Flight: Jason Sebastian1; Greg Olson2; 1QuesTek Innovations; 2QuesTek & Northwestern University
QuesTek Innovations, a leader in the field of Integrated Computational Materials Engineering (ICME), will present a “success story” overview of the development of their new ultra-high strength, high performance structural steel, FerriumŪ M54™. The development of this alloy was sponsored under a U.S. Navy-funded Small Business Innovation Research (SBIR) program with the goal of developing a cost competitive, drop-in replacement for AerMetŪ100 aerospace alloy. A variety of ICME- and “Accelerated Insertion of Materials (AIM)”-type computational models were employed during the design and development of M54, and highlights will be presented. M54’s overall development progressed from a clean sheet design in 2007 to a precise chemical composition in less than one year, and the first 10-ton VIM/VAR ingot was produced the following year. An Aerospace Material Specification (AMS 6516) was issued two years later, and inclusion in the MMPDS handbook for A- and B- basis design minima was approved in December 2013. QuesTek coordinated the production and qualification of hook shank components made from M54 that were successfully flight tested in December 2014. Highlights will be presented from a recent (August 2016) National Institute of Standards and Technology-funded case study (carried out by Nexight Group and Energetics Incorporated) detailing overall timeline of the successful development of M54 and its application to U.S. Navy hook shanks. Results and data for M54 will be presented from throughout the alloy development process, with a focus on the properties that distinguish it from legacy materials. Highlights of recent M54 application and commercialization activities will also be presented.
CASM: Design Principles, Recent Progress, and Collaborative Opportunities: Brian Puchala1; John Thomas2; Anton Van der Ven2; 1University of Michigan, Ann Arbor; 2University of California, Santa Barbara
Cluster expansion effective Hamiltonians provide a rigorous link between very accurate atomistic scale first principles calculations and very efficient meso- and macro-scale continuum methods for describing materials thermodynamics and kinetics. To implement these methods we are developing the open source software package CASM (github.com/prisms-center/CASMcode). CASM automates the process for 1) formulating effective Hamiltonians based on the symmetry of the crystal system and relevant atomistic degrees of freedom, 2) parameterizing effective Hamiltonian coefficients from first principles calculations, and 3) calculating finite temperature thermodynamic and kinetic properties, such as composition and strain-dependent free energies and diffusion coefficients, using Monte Carlo methods. In this talk I will present CASM design principles and concepts, recent progress, and the direction of its near-term development. I will highlight opportunities for collaborative development of new features and integration with methods at lower and higher length scales. Developed with support from the Center for PRedictive Structural Materials Science (PRISMS) at the University of Michigan, CASM provides an essential component for integrated computational materials engineering.
Materials Informatics and Big Data: Realization of 4th Paradigm of Science in Materials Science
: Ankit Agrawal1; Alok Choudhary1; 1Northwestern University
In this age of “big data”, large-scale experimental and simulation data is increasingly becoming available in all fields of science, and materials science is no exception to it. Our ability to collect and store this data has greatly surpassed our capability to analyze it, underscoring the emergence of the fourth paradigm of science, which is data-driven discovery. The need to use of advanced data science approaches in materials science is also recognized by the Materials Genome Initiative (MGI), further promoting the emerging field of materials informatics. In this talk, I would present some of our recent works employing state-of-the-art data analytics for exploring processing-structure-property-performance (PSPP) linkages in materials, both in terms of forward models (e.g. predicting property for a given material) and inverse models (e.g. discovering materials that possess a desired property). Some examples include developing models for predicting fatigue strength of steel alloys, data-driven discovery of stable compounds, and microstructure optimization of a magnetostrictive Fe-Ga alloy. I will also demonstrate some online web-tools we have developed that deploy machine learning models to predict materials properties.Such data-driven analytics can significantly accelerate prediction of material properties, which in turn can accelerate the optimization process and thus help realize the dream of rational materials design. The increasingly availability of materials databases along with groundbreaking advances in data science approaches offers lot of promise to successfully realize the goals of MGI, and aid in the discovery, design, and deployment of next-generation materials.
HPC4Manufacturing Program: A National Laboratory - Industry Partnership in High Performance Computational Simulations for Energy Efficiency: Robin Miles1; Peg Folta1; Jeff Roberts1; 1Lawrence Livermore National Laboratory
The HPC4Manufacture program is a new EERE-sponsored program with the aims of introducing industry to High Performance Computing for advanced science and engineering simulations, transferring advanced simulation techniques developed at the National Laboratories to industry and reducing industrial energy usage. The three partner national laboratories have been working with a variety of large and small companies in a variety of energy intensive industries to improve manufacturing processes and enhance product design. Examples include optimizing steel-making furnaces to reduce energy and coke usage and advanced CFD modeling of turbines used for aerospace and energy generation. Many companies are interested in advanced simulation as a way to reduce costs associated with product/or and process testing. An overview of the program will presented and example projects discussed.
ICME in Design of Hard Materials and Substitution of Critical Raw Materials: Anssi Laukkanen1; Tatu Pinomaa1; Tom Andersson1; Matti Lindroos1; Tomi Suhonen1; Kenneth Holmberg1; 1VTT
The Process-Structure-Properties-Performance (PSPP) paradigm is emerging as one of the cornerstones of implementing integrated computational materials engineering (ICME) for materials R&D needs, such as discovery and development of novel material solutions, optimization and tailoring of product specific materials, and overall troubleshooting materials affiliated problems. We present a case study employing an in-house multiscale materials modeling toolset in design of WC-Co hard materials and TiC-Ni critical raw material substitutes. The approach merges phase field and kinetics modeling of material processing to imaging based modeling of material nano-microstructure to establish causal material properties and performance under typical application environments. Computation driven material design aspects are addressed by an informatics solution incorporating evolutionary computing and machine learning. The results demonstrate how ICME can be applied in designing novel composite materials and finding substitute candidates.