4th World Congress on Integrated Computational Materials Engineering (ICME 2017): Microstructure Evolution - III
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
Tuesday 8:00 AM
May 23, 2017
Room: Salon II, III
Location: Ann Arbor Marriott Ypsilanti at Eagle Crest
Microstructure Recognition and Analysis by Advanced Machine Learning (P-37): Yoshitaka Adachi1; 1Kagoshima University
Human being can recognize a microstructure of metals and then extract its features manually based on standard metallography method. It is very important for metallurgists to understand correlation between a microstructure and a property. However it seems time-consuming to analyses microstructures by hand. The process how human being gets information from micrographs should be clarified to replace the role of human being with of computer on microstructure recognition. This study made an attempt to apply deep learning to quantify microstructures. An approach to microstructure quantification by convolutional neural network and advanced image processing will be demonstrated.
8:20 AM Cancelled
The Microstructural Role: A Size Effect Approach (P-57): Daniel Rodriguez Galan1; Javier Segurado1; Ignacio Romero1; 1IMDEA Materials
A vast and long-standing body of experimental evidence conclusively establishes the fact that the yield strength of crystals is size-dependent. This size dependence can be exploited to fabricate materials combining both high strength and ductility, e.g., by the equal channel angular pressing (ECAP) process (Rodríguez-Galán et al, 2015), and in other ways. In order to optimize the beneficial properties of grain refinement, it is necessary to understand the deformation micromechanisms governing the mechanical behaviour. These mechanisms depend on the refined grain size and also on other microstructural features, such as grain boundaries state, defect densities and crystallographic texture. However, the grain size plays a fundamental role. At this moment, non-local theories allow us to capture the size effect. However, these theories present a lot of challenges that are necessary to solve. We present an approach based on non-local theories with the objective to obtain the size effect in a natural way, to emphasize on numerical part of the problem.
An Integrated Solidification and Heat Treatment Models for Predicting Mechanical Properties of Cast Aluminum Alloy Component: Chang Kai Wu1; Salem Mosbah2; 1Dow Performance Silicones; 2Think Solidification
In this work, a newly developed modeling tool is presented which computes the local mechanical properties of cast and precipitation hardening heat treated aluminum alloy component. The integrated model simulates both casting and heat treating processes, and it computes the local hardness, yield strength and ultimate tensile strength, that developed in the casting during each step. Both alloy solidification and precipitation hardening heat treatment steps are simulated. The solidification model takes into account grains nucleation and the mushy zone front undercooling to predict the growth of the dendritic and eutectic microstructures. The predicted secondary dendrite arm spacing (SDAS) map is used to calculate the local strengths in the subsequent heat treatment steps. The heat treating model takes into account quenching and aging steps. The integrated model uses an extensive database that was developed specifically for the A356 alloy under consideration. The database includes temperature dependent mechanical, physical, and thermal properties of the alloy.
Modelling and Experimental Characterization of Microstructure Evolution during Cooling Stage of Homogenization Heat Treatment of Al-Mg-Si Alloys: Qiang Du1; 1SINTEF
A CALPHAD-coupled multi-component multi-phase Kampmann-Wagner Numerical modelling framework, implemented in the software called PreciMS, has been employed to predict the precipitation of the stable and metastable phases, i.e., β (Mg2Si) and β' (Mg18Si10) during the cooling process within a homogenization heat treatment of AA6xxx alloys. The model is able to treat the concurrent nucleation and growth of the multiple phase particles during this non-isothermal process, and predict the evolutions of the precipitating particles' size distribution and fraction. The model predictions have been validated by the microstructure characterization carried out with Optical Microscopy, Scanning Electron Microscopy, Transmission Electron Microscopy and Electrical Resistivity Measurement on the samples from some dedicated homogenization heat treatment experiments of AA6xxx alloys. It is concluded that the proposed model is a valuable tool in optimizing and designing alloy chemistries and cooling process parameters.
Precipitates Strengthening using Dislocation Dynamics: Sylvie Aubry1; Tom Arsenlis1; 1LLNL
Predicting the influence of precipitate characteristics on the strength of selected aluminum-lithium alloys for a variety of heat treatment conditions has important applications for the aircraft industry. Currently, aircraft hybrid fan blades are made of titanium. Replacing these blades by aluminum-lithium alloys has been shown to lead to great savings in fuel consumption. The ability to model and predict the mechanical response of these alloys as a function of material processing parameters allows optimization of current forgings and future designs. As part of a multiscale approach the dislocation dynamics method has been used to predict the strength of materials. An extension of the dislocation dynamics method is presented. It takes precipitates into account. Interactions of dislocations defect with ellipsoidal precipitates is modelled. Large scale simulations of theta prime and T precipitates are presented. The stress/strain response as a function of precipitate characteristics are shown and explained. Lawrence Livermore National Laboratory is operated by Lawrence Livermore National Security, LLC, for the U.S. Department of Energy, National Nuclear Security Administration under ContractDE-AC52-07NA27344.
Mutiscale Modelling of θ' Precipitation during Aging of Al-4wt.%Cu Alloys: Hong Liu1; Gustavo Esteban-Manzanares1; Bárbara Bellón1; Ilchat Sabirov1; Javier LLorca2; 1IMDEA Materials Institute; 2Polytechnic University of Madrid/IMDEA Materials Institute
The strength of Al-Cu alloys is controlled by the size, shape, orientation and spatial distribution of θ' precipitates that hinder dislocation slip but there are not multiscale simulations tools that can predict the features of these precipitates during high temperature aging. In this investigation, the evolution and equilibrium morphology of the θ' precipitates in 3 dimensions during high temperature aging is studied by means of a multiscale approach. The lattice parameters and elastic constants of θ' precipitates and of the α-Al matrix were calculated using first principles density functional theory, whereas the interfacial energy between θ' phase and α-Al matrix was determined by means of molecular dynamics. The equilibrium shape and the evolution of θ' precipitates with and without including the presence of dislocations was studied using the phase field method. The simulations indicate the plate-like shape of the θ' precipitates comes about from the competition of the elastic strain energy and the interfacial energy. Moreover, the high aspect ratio of θ' precipitates is induced by the shear strain and interfacial energy anisotropy. It is shown that the stress field of pre-existing dislocation may result in a series of parallel θ' precipitates forming along the dislocation line. Finally, the results of the multiscale simulations in terms of precipitate shape, size and spatial distribution are compared with detailed transmission electron microscopy observations on Al-4 wt. % Cu alloys that were aged at 180ºC for up to 30 hours.
10:00 AM Break
Linked Heat Treatment and Bending Simulation of Aluminum Tailored Heat Treated Profiles: Hannes Fröck1; Matthias Graser2; Michael Reich1; Michael Lechner2; Marion Merklein2; Olaf Kessler1; 1University of Rostock; 2Friedrich-Alexander-Universität Erlangen-Nürnberg
Precipitation hardening aluminum alloys enable tailoring of mechanical properties by the dissolution of strength-increasing precipitates during a local short-term heat treatment. Tailored Heat Treated Profiles (THTP) are aluminum extrusion profiles with locally different material properties, specifically optimized for succeeding bending processes. Softened areas need to be generated next to hardened areas to optimize the material flow during the forming process. To determine the optimized layout of softened and hardened areas, a process chain simulation consisting of the simulation of the short-term heat treatment and the subsequent forming process seems purposeful. The numerical modeling of short-term heat treatment requires a coupled computation of thermal and mechanical simulation with particular focus on the evaluation of microstructure and consequently on the change of mechanical properties. The dissolution and precipitation behavior during heating and cooling of aluminum profiles 6060 T4 is investigated using differential scanning calorimetry. Thermo-mechanical analysis is applied for evaluation of the mechanical properties. This behavior should be described in a material model with the software LS DYNA. The heat treatment simulation provides a distribution of mechanical properties along the profile, which is an important input parameter for the following forming simulation. In order to avoid a loss of information between the heat treatment simulation and forming simulation, both linked simulations are performed with the software LS DYNA.
Numerical Simulation of Meso-micro structure in Ni-based Superalloy during Liquid Metal Cooling Process: Xuewei Yan1; Wei Li2; Lei Yao2; Xin Xue2; Yanbin Wang2; Gang Zhao2; Juntao Li2; Qingyan Xu1; Baicheng Liu1; 1Tsinghua University; 2Beijing CISRI-GAONA Materials & Technology Co. LTD
Ni-based superalloys are the preferred material to manufacture turbine blades for their high temperature strength, microstructural stability and corrosion resistance. As a new method, liquid-metal cooling (LMC) process is prospective used in manufacturing large-size turbines blades. Unfortunately, there are many casting defects during LMC directional solidification, such as stray grain, freckle, cracking. Moreover, the trial and error method is time and money cost and lead to a long R&D cycle. As a powerful tool, numerical simulation can be used to study LMC directional solidification processes, to predict final microstructures and optimize process parameters. Mathematical models of microstructure nucleation and growth were established based on the cellular automaton-finite difference (CA-FD) method to simulate meso-scale grain and micro dendrite growth behavior and morphology. Simulated and experimental results were compared in this work, and they agreed very well with each other. Meso-scale grain evolution and micro dendritic distribution at a large scale were investigated in detail, and the results indicated that grain numbers reduced with the increase of height of the casting, and stray grain will be relatively easy to produce in the platform. In addition, secondary dendrite arms were very tiny at the bottom of the casting, and they will coarsen as the he height of the cross section increased.
A Crystal Plasticity (CP) Model for Dynamic Recrystallization (DRX) in Two Phase Titanium Alloys: Riddhiman Bhattacharya1; Veera Sundararaghavan1; John Allison1; 1University of Michigan, Ann Arbor
Titanium (Ti) alloys are attractive candidates for bladed disk (BLISK) manufacturing due to their high specific strength and retention of mechanical properties up to high temperatures (~500 degree C). However, their susceptibility to contamination in the molten state necessitates use of solid state processing methods, such as Linear/Translation Friction Welding (LFW/TFW). In this process, simultaneous action of strain and temperature at or near the weld interface causes Dynamic Recrystallization (DRX), manifested in the form of fine recrystallized beta grains in a two phase (alpha+beta) alloy. The constitutive response of this phenomenon is experimentally studied and input into an advanced Crystal Plasticity (CP) framework. The model is able to capture the softening in stress-strain behavior occurring due to DRX and predict the recrystallization texture. Future work is directed at predicting the recrystallized microstructure based on certain nucleation conditions and mesh refinement criteria.
Crystal Plasticity Model For Two Phase Ti-6Al-4V Incorporating Microstructural Variability: Kartik Kapoor1; Ryan Noraas2; Vasisht Venkatesh2; Michael Sangid1; 1Purdue University; 2Pratt & Whitney
Dual phase titanium alloys can be designed and processed to exhibit a wide range of properties depending on component requirements. There is a growing need to understand damage mechanisms in two-phase titanium alloys, such as Ti-6Al-4V, due to their widespread use in the aerospace industry. Ti-6Al-4V microstructures consist of an alpha (HCP) phase and a beta (BCC) phase. In this work, a crystal plasticity finite element (CPFE) model that explicitly incorporates both these phases, and hence the anisotropy between them is developed. The finite element microstructural mesh used for the CPFE simulations is created using data obtained from electron backscatter diffraction (EBSD) and backscatter electron (BSE) imaging with the former providing the grain orientation and morphology and the latter giving information on the phases. Utilization of this approach ensures that the finite element mesh truly represents the actualmicrostructure of the material. Further, the CPFE model developed is calibrated over a range of different microstructures, including varying beta volume fractions. Since Ti-6Al-4V components can be manufactured to meet a range of microstructure and property requirements, a robust crystal plasticity model for this alloy should be valid over a range of heat treatment variations and associated microstructures. Finally, the implications of this work looks at linking microstructural features to damage in two-phase titanium alloys.
CALPHAD Modeling Tools for ICME Applications: Fan Zhang1; Shuanglin Chen1; Weisheng Cao1; Chuan Zhang1; Jun Zhu1; 1CompuTherm, LLC
Integrated Computational Materials Engineering (ICME) has recently been highlighted as a methodology that can unlock great potential for significant benefits in cost-effective materials and process design. Optimization of alloy chemistry and processing conditions, which is the common practice of materials scientists/engineers working on materials design and improvement, is no longer based on trial-and-error approaches. With the recent advancement of computer science and modern information technology, alloy design process can be greatly accelerated with the aid of computational tools. While the initiative of ICME and MGI has motivated the use and development of modeling tools, the CALPHAD-based modeling tools have been used for alloy design for more than 20 years. The CALPHAD method, which was first developed for the calculation of multi-component complicated phase diagrams, has now been applied to variety fields of materials science and engineering. CALPHAD-based modeling tools have extended their capability from calculating phase stability and thermodynamics of a materials system to simulating precipitation and diffusion kinetics. These modeling tools have been used by ICME practitioners on daily basis to accelerate alloy design and development. In this presentation, we will give a brief introduction on the modeling tools developed at CompuTherm based on the CALPHAD method. Unique features of our modeling tools, such as contour diagrams, high-throughput calculations, will be highlighted. We will then use examples to demonstrate the successful applications of these modeling tools in ICME and MGI.