Session Sheet - 8th World Congress on Integrated Computational Materials Engineering (ICME 2025): ICME Application to Advanced Manufacturing I

8th World Congress on Integrated Computational Materials Engineering (ICME 2025): ICME Application to Advanced Manufacturing I
Program Organizers: Victoria Miller, University of Florida; Stephen DeWitt, Oak Ridge National Laboratory

Tuesday 9:00 AM
June 17, 2025
Room: Platinum Ballroom 5
Location: Anaheim Marriott

Session Chair: Deepali Patil, Worcester Polytechnic Institute

9:00 AM  Cancelled
ICME Tools for In-Space Welding: Ellis Crabtree¹; Andrew O'Connor¹; Fredrick Michael¹; Louise Littles¹; Jeffrey Sowards¹; ¹NASA Marshall Space Flight Center
    The recent boom of the in-space economy has demonstrated need for continued development of electron beam welding (EBW) and laser beam welding (LBW) processes, which are desirable for their compactness, low mass, low power consumption, and high wall plug efficiency. Demonstrating, developing, and applying welding processes is physically difficult, and costs are high to develop and fly individual space-based trials. This drives the current approach to develop ICME physics-based models in tandem with CALPHAD techniques. In this work, a thermal model of Skylab EBW experiments is established and compared to empirical data. The model is used to show variation between Earth-based and in-space weld structure and properties through exploration of key variables that define the Low earth orbit and lunar surface space environments, namely temperature, pressure, and gravity. Finally, physical processes associated with heat and mass transport during welding are evaluated through several case studies demonstrating need for further research.

9:30 AM
An ICME Approach to Establish Causal Links Between Process Induced Microstructures and Material Properties in Austenitic Steels: Sourabh Supanekar¹; Hector Basoalto¹; ¹University of Sheffield
     Integrated Computational Materials Engineering (ICME) offers a robust framework for quantifying the causal relationships between welding process parameters and resulting material properties, a critical capability for optimizing engineering performance. This study develops a multiscale, physics-based material model to predict the impact of key welding parameters—including power and velocity of heat source input —on microstructural evolution and mechanical properties in austenitic steels. By integrating cellular automaton (CA) techniques with finite element analysis (FEA), we accurately simulate process-induced microstructures and the distribution of residual stresses within the welded joints. These simulations establish causal links between welding parameters and finalproperties, allowing for precise prediction and control of material properties such as hardness, toughness, and fatigue resistance. This ICME-driven methodology highlights the potential of computational models to advance materials design and process optimization in welding, leading to enhanced reliability and performance across manufacturing applications.

9:50 AM
Material Physics Governing Rotary Friction Welding: Miguel Espadero¹; Hector Basoalto¹; Simon Bray²; Peter Steven²; ¹University of Sheffield; ²Rolls-Royce plc
    The aim of this study is to develop a physics-based constitutive framework which enables the simulation of the thermo-mechanical fields and the microstructural evolution during rotary friction welding of precipitate-strengthened nickel-based superalloys. The primary objective is to describe the micro-mechanisms governing the flow stress behaviour during the different welding phases of the inertia welding process. A dislocation slip model has been proposed which considers the dislocation-precipitate interactions in the derivation of the plastic shear strain rates. The model has successfully studied the effect of the different materials variants for the same weld, showing it is able to replicate the response observed in experiments. One of the most valuable aspects of the framework is its ability to analyse model variables as plastic strain, volume fraction or dislocation density. By doing this, a deeper understanding of the underlying mechanisms at each stage of the process can be achieved.

10:10 AM
A Mechanistic Deposition Efficiency Model for Cold-Spraying Dissimilar Materials: Christian Brandl¹; ¹The University of Melbourne
     Cold spray (CS) composite coatings created from mixed powders can demonstrate improved strength and corrosion resistance compared to coatings made from pure metals. However, controlling the deposition performance and the resulting microstructure during the cold spray process is challenging because the complex relationship between the different material properties dictates additional process constraints.This study combines mechanistic models for particle impact velocities and critical velocities necessary for particle adhesion to predict the formation of CS layers for relevant processing parameters. The findings outline the implications for composition gradients and the optimal operating parameters. Our model enables us to identify the required processing conditions and constraints for metal matrix composite coatings within Integrated Computational Materials Engineering frameworks to optimise processing for targeted material performance.

10:30 AM Break

10:50 AM
Multiscale Computational Framework for Optimization of Processing Parameters in Shear-Assisted Processing and Extrusion (ShAPE) of Nuclear Cladding Materials: Lukasz Kuna¹; Lei Li¹; Shadab Shaikh¹; Mageshwari Komarasamy¹; Mohan Sai Kiran Kumar Yadav Nartu¹; Jens Darsell¹; Isabella van Rooyen¹; Stuart Malloy¹; Ayoub Soulami¹; ¹Pacific Northwest National Lab
    This work aims to develop a multiscale and multiphysics computational framework to reveal insight into the process-structure-property relationship in shear-assisted processing and extrusion (ShAPE) of nuclear cladding materials for applications in challenging environments. In the developed framework, ShAPE is simulated using meshfree smoothed particle hydrodynamics (SPH) to obtain thermomechanical responses at the macroscale and utilized to inform thermodynamic simulations at the mesoscale. The temperature and strain data predicted by the SPH model serve as inputs to a mesoscale phase field and crystal plasticity (PF-CP) coupled model to simulate microstructure and texture evolutions, as well as the processed material residual properties. Ultimately, the multiscale SPH-PF-CP model will be validated with experimental data and used to establish process-structure-property relationships. The multi scale framework will inform optimization of ShAPE processing parameters to achieve desired microstructures for various types of high entropy alloys and oxide dispersion-strengthened steels.

11:10 AM
Utilizing Crystal Plasticity Surrogate Models in Finite Element Analysis of Incremental Sheet Forming: John Weeks¹; Aaron Stebner¹; ¹Georgia Institute of Technology
    Incremental sheet forming (ISF) demonstrates increased design flexibility, cost-effectiveness, and expanded design spaces for small-lot productions compared to conventional forming. During ISF, targeted deformation processing enables local material properties and microstructures which may be modeled using ICME techniques such as multiscale crystal plasticity (CP) simulations. However, multiscale modeling of ISF is expensive due to changing contact definitions, large deformations, and evaluation of CP models. In this work, we use a recurrent neural network as a surrogate model for CP to enable efficient multiscale ISF simulations. We integrate a visco-plastic self-consistent CP model (VPSC8) into a finite element framework (ABAQUS/Explicit) via a VUMAT. We demonstrate an effective workflow for data generation, training, validation, and implementation for multiple materials. This approach is applied to FCC aluminum to show the advantages of ICME in modeling these processes and how this approach can be used to guide design decisions in ISF.

11:30 AM  Cancelled
Particle Simulation for Powder Metallurgy Hot Isostatic Pressing: Sam Reeve¹; Pablo Seleson¹; Austin Isner¹; Yousub Lee¹; ¹Oak Ridge National Laboratory
    We demonstrate CabanaPD, a unified simulation tool for powder-based advanced manufacturing, focusing on powder metallurgy hot isostatic pressing (PM-HIP). PM processing routes are crucial for complex component manufacturing. Simulation for powder filling and powder consolidation for PM-HIP is primarily done today with the discrete element method (DEM) and finite element method (FEM), respectively. For both, CPU-only codes, GPU codes which are not portable across hardware architectures, and/or commercial codes are used, substantially limiting the applicability for the potentially billions of particles necessary for filling and consolidation of industrially relevant components. CabanaPD, an open source peridynamics code, has recently been expanded for PM-HIP including a new DEM module for powder filling, expanded boundary conditions, models for continuum powder consolidation, and conversion from powder to continuum scales. CabanaPD builds on the Cabana and Kokkos libraries for scalability and performance portability enabling simulation from local workstations to U.S. Department of Energy leadership supercomputers.

11:50 AM
Performance Analysis of Different Shaped Tool Electrodes During Ultrasonic Assisted Electrical Discharge Machining (UAEDM) of Inconel 718: Shankar Singh¹; ¹Sant Longowal Institute of Engineering & Technology (SLIET), Longowal
     Ultrasonic Assisted Electrical Discharge Machining (UAEDM) is a hybrid machining process in which small amplitude vibrations of ultrasonic frequency are imparted to either electrode, work material or dielectric fluid in conventional EDM process, for effective flushing, hence leading to improved efficiency and consistency. The present study presents UAEDM of Inconel 718 work material. During experimentation, process parameters namely copper tool electrode geometry (circular and square) vibrated at 20 KHz frequency, discharge current, servo voltage, pulse on duration, pulse off duration and tool lift time were varied to find their effect on response characteristics i.e., material removal rate, surface roughness and electrode wear rate. Experiments have been performed according to Taguchi’s L18 mixed-level orthogonal array. Multiple objective optimization of performance characteristics have been done using Taguchi based Grey Relational Analysis (TGRA) technique. Furthermore, surface morphology, metallurgical characteristics (Phases, crystallite size) and microhardness of the machined surface are also studied.