6th World Congress on Integrated Computational Materials Engineering (ICME 2022): ICME for Non-Metals, Structural Composites, and Ceramics
Program Organizers: William Joost; Kester Clarke, Los Alamos National Laboratory; Danielle Cote, Worcester Polytechnic Institute; Javier Llorca, IMDEA Materials Institute & Technical University of Madrid; Heather Murdoch, U.S. Army Research Laboratory; Satyam Sahay, John Deere; Michael Sangid, Purdue University
Thursday 9:00 AM
April 28, 2022
Room: Regency Ballroom AB
Location: Hyatt Regency Lake Tahoe
Session Chair: Marianna Maiaru, University of Massachusetts Lowell
9:00 AM Invited
Implementing Reactive Molecular Dynamics Simulations to Predict Residual Stresses in Polymers Using ICME: Sagar Patil1; Khatereh Kashmari1; Sagar Shah2; Prathamesh Deshpande1; Gregory Odegard; Marianna Maiaru2; 1Michigan Technological University; 2University of Massachusetts Lowell
High-performance resins are extensively used as matrix material in composites for aerospace applications which require a wide range of elevated temperatures during their manufacturing. The shrinkage cause during curing contributes to the residual stress build-up that can be detrimental to composite laminates under in-service loading. In thermosets like epoxy resins shrinkage causes due to crosslinking between monomers, and in thermoplastics highly densified crystalline regions can form in the leading to shrinkage of the matrix and development of internal residual stresses. The prediction of residual stresses requires models that combines simulation tools at multiple length-scales. Integrated Computational Materials Engineering (ICME) is an excellent tool which make a bridge between different length scales by using computational and experimental methods and provides an optimal approach in terms of cost and time to designing composite materials. Here, a multi-scale framework, based on ICME, which integrates molecular dynamics (MD) at nanoscale and finite element methods (FEM) at micro-scale is used to investigate the effects of temperature history and processing conditions on the thermal-mechanical properties of EPON862/DETDA epoxy and PEEK and predict the evolution of residual stress in a polymer matrix composites during processing. This information plays a key role in multiscale process modeling necessary to establish ideal processing conditions to yield composites with optimal performance and durability. The results showed that molecular and microscale analyses can be successfully integrated under ICME to investigate the residual stress build-up during composite processing.
9:30 AM
Molecular Dynamics Simulation-Based Polymer Matrix Composite Model: Xiawa Wu1; 1Penn State Behrend
Predicting the damage and failure of polymer matrix composites (PMCs) is of crucial interest for their reliable performance in the aerospace industry. In this work, a coarse-grained molecular dynamics (CG-MD) model has been developed to characterize the evolution of free volume density in DGEBA polymers under loading and its subsequent plastic deformation. A detailed atomic monomer is coarsened to create the tailored plastic behavior. Cross-linked polymer networks are created under different curing conditions using a dynamic cross-linking algorithm. The free volumes are measured as a function of strain by fitting the largest ellipsoids between neighboring chains in the network. From these simulations, we develop a direct correlation between the evolution of plastic deformation and the free volume density. The results of these simulations are then upscaled into finite element simulations to model the damage and failure of PMCs.
9:50 AM
Multi-Objective Optimization of CALPHAD and Empirical Models to Discover New High-Temperature
metallic Glasses: Jerry Howard1; Krista Carlson; Leslie Mushongera; 1University of Nevada Reno
Metallic glasses (MGs) are an emerging class of materials possessing high strength, high corrosion resistance, and ease of fabrication when compared to their crystalline counterparts. However, most previously studied MGs are not useful in high temperature environments because they undergo the glass transition phenomenon and crystallize below the melting point, leading to loss of beneficial properties provided by the glassy state. In addition, good glass-forming alloys are typically located near regions of low melting temperature, exacerbating further the issue of poor high-temperature performance. We have developed and validated a new tool for the discovery of high-temperature stable MGs known as GenMG. This tool effectively couplesempirical predictions of glass forming ability with computational thermodynamics through a multi-objective optimization genetic algorithm. This tool has been designed to be both transferable to any reasonable alloy composition and extensible to multi-component alloy systems.
10:10 AM
Process Modeling of Virtually Reconstructed Composites with ICME: Sagar Shah1; Marianna Maiaru; 1University of Massachusetts Lowell
ICME increasingly recognizes that processing conditions during manufacturing induce microstructural variations, which result in large scatters in the bulk composite properties. In order to quantify such variations and their effect on the bulk properties, it is critical to establish the Processing-Microstructure-Property relationship. The authors have previously successfully quantified the process-induced geometrical and physical variations in the composite microstructure with techniques such as statistical analysis (micro-CT scans of composite microstructure) and micro-Raman spectroscopy, respectively. Present work describes the development and working of a process modeling platform to virtually cure and test the artificially reconstructed laminates. Previously developed statistical metrics aid in the virtual reconstruction of Representative Volume Elements (RVEs) in a finite element framework. While accounting for the geometrical variations in the microstructure, the virtual cure analysis of said RVEs can successfully predict the in-situ matrix behavior. Virtual mechanical tests are performed to predict composite properties using progressive damage models.