ICME 2023: ICME Des Tools: IV
Program Organizers: Charles Ward, AFRL/RXM; Heather Murdoch, U.S. Army Research Laboratory
Thursday 9:00 AM
May 25, 2023
Room: Boca I-III
Location: Caribe Royale
Session Chair: Paul Mason, Thermo-Calc Software Inc.
9:00 AM Invited
An ICME Based Approach for Improving High-strength Ni Alloy Process Yield: Shankarjee Krishnamoorthi1; Vahid Tari1; John Foltz1; Ramesh Minisandram1; 1ATI Specialty Materials
High strength Nickel alloys are widely used in aerospace applications to make critical components due to their excellent thermomechanical properties. The processing of manufacturing Ni ingots is an energy intensive process which starts with melting and subsequent thermomechanical processing. A typical Nickel alloy is melted 2 to 3 times (VIM/VAR/ESR), and the thermomechanical processing typically involves multiple press and radial forging reductions, reheats in furnaces, and heat treatments to achieve the required grain size and mechanical properties for aerospace and petrochemical applications. Even under controlled conditions, variation in the final product can occur including surface cracks, hidden porosity, undesired grain size, etc. leading to rework and or reprocessing. We will layout and discuss an ICME-based approach to improve the process yield, tracing the billet through its journey from melting to thermomechanical processing while utilizing continuum-modeling and thermodynamics-based models. We will elaborate on the results, challenges, and potential future steps.
9:30 AM
ICME Modeling of Can Body Stock: Waqas Muhammad1; Abhijit Brahme1; Kaan Inal1; Chal Park2; Aaditya Lakshmanan2; Sazol Das2; 1University of Waterloo; 2Novelis
Each year billions of aluminum beverages cans are manufactured, which means can body stock, made of AA3104, has one of the largest aluminum markets globally. Production of can body stock involves multiple key manufacturing steps, starting with large-scale DC casting, homogenization step, and a series of hot and cold rolling down to the final gauge. Since AA3104 is non heat-treatable alloy, the resulting microstructure from the final rolling steps will ultimately determine properties and performance of the can body stock. Therefore, it becomes important to develop a numerical tool that can quantitatively capture microstructure evolution during production. In this work, an ICME framework is developed to predict crystallographic texture, recrystallization, and distribution of intermetallic particles in AA3104 during hot and cold rolling processes. The framework demonstrated that it could capture evolution of microstructure of interest with sufficient accuracy as well as be used to provide suggestions to improved rolling schedules.
9:50 AM
Digital Threads for FAST Processing: Lucia Scotti1; Martin Jackson1; Oliver Levano Blanch2; Beatriz Fernandez Silva2; Sam Lister1; Prashant Jadhav1; Hugh Banes1; Magnus Anderson1; Hector Basoalto1; 1University of Sheffield; 2Rolls-Royce Plc
Field assisted sintering technology (FAST) is a manufacturing process for near-net shape components. The mechanical behaviour of the final part depends on the process recipe (dwell temperature, dwell time, load/pressure, heating rate, and electric current waveform), which is usually selected through user experience and extensive experimental trials. Digital threading of sensor data to physics-based computational models and vice versa promises to reduce the cost of the optimisation process and retains the know-how that can be lost when the workforce changes.The proposed digital thread implementation allows users to feed the temperature history and applied force from the FAST machine to modelling tools to add new data sets of phase transformation and macro-mechanics behaviour. The new enriched data-set will enable users to make informed decisions and optimise the process for new alloys and powder morphologies, reducing energy consumption and meeting the performance of the final part.
10:10 AM
Machine Learning-enhanced Robust Co-design Exploration for Many Objective, Multilevel Materials Design Problems: Anand Balu Nellippallil1; Mathew Baby1; Rashmi Rama Sushil2; Palaniappan Ramu2; Janet K. Allen3; Farrokh Mistree3; 1Florida Institute of Technology; 2IIT Madras; 3University of Oklahoma
ICME requires seamless integration and exploration of material, product, and manufacturing process design spaces across multilevel. This demands the capability to co-design, that is, share ranged sets of robust design specifications among distributed material, product, and manufacturing process stakeholders through the visualization and exploration of high-dimensional material design space under uncertainty.In this paper, we present a machine learning-enhanced robust co-design exploration framework by integrating robust compromise decision support problem construct (r-cDSP) with interpretable self-organizing maps (iSOM). Using the framework, we facilitate systematic and efficient visualization, interpretation, and exploration of high-dimensional materials design space under uncertainty. The generic nature of the framework for multidisciplinary designers to a) understand the interactions and capture the dominant process mechanisms that affect materials responses and b) provide decision support for problems involving many conflicting goals under uncertainty is demonstrated using an industry-inspired steel manufacturing process chain problem.
10:30 AM
Integrating Crystal Plasticity and Thermo-mechanical Constitutive Modeling: Anderson Nascimento1; Akhilesh Pedgaonkar2; Curt Bronkhorst2; Irene Beyerlein1; 1University of California, Santa Barbara; 2University of Wisconsin-Madison
Given the importance of temperature in the dislocation density of crystalline materials, constitutive thermo-mechanical models provide a pathway for a more accurate description of temperature-sensitive processes. Commonly, however, the thermo-mechanical description of the material response is limited to phenomenological macroscopic models with limited interpretability. Here, thermal expansion is included in the single crystal constitutive response via an eigenstrain contribution to the deformation gradient, and a fully coupled implicit thermo-mechanical formulation is implemented into the variational framework of the crystal plasticity finite element method. Such a thermodynamically consistent model with temperature and micromechanical fields is used to investigate the response of different materials under thermal-stress boundary conditions.
10:50 AM Break