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Über dieses Buch

This book represents a collection of papers presented at the 4th World Congress on Integrated Computational Materials Engineering (ICME 2017), a specialty conference organized by The Minerals, Metals & Materials Society (TMS). The contributions offer topics relevant to the global advancement of ICME as an engineering discipline. Topics covered include the following:ICME Success Stories and ApplicationsVerification, Validation, Uncertainty Quantification Issues and Gap AnalysisIntegration Framework and UsageAdditive ManufacturingPhase Field ModelingMicrostructure EvolutionICME Design Tools and ApplicationMechanical Performance Using Multi-Scale Modeling



Integration Framework and Usage


An Attempt to Integrate Software Tools at Microscale and Above Towards an ICME Approach for Heat Treatment of a DP Steel Gear with Reduced Distortion

Finite element simulation of heat treatment cycles in steel could be challenging when it involves phase transformation at the microscale. An ICME approach that can take into account the microstructure changes during the heat treatment and the corresponding changes in the macroscale properties could greatly help these simulations. Dual phase steel (DP steel)DP steel are potential alternate materials for gearsGear with reduced distortion. Inter-critical annealingInter-critical annealing in DP steel involves phase transformation at the microscale and the finite element simulation of this heat treatment could be greatly improved by such an ICME approach. In the present work, phase field modeling implemented in the software package MicressMicress is used to simulate the microstructure evolution during inter-critical annealing. Asymptotic HomogenizationHomogenization is used to predict the effective macroscale thermoelastic properties from the simulated microstructure. The macroscale effective flow curves are obtained by performing Virtual Testing on the phase field simulated microstructure using Finite Element MethodFinite element method. All the predicted effective properties are then passed on to the macro scale Finite Element simulation software SimufactSimufact Forming, where the heat treatment cycle for the inter-critical annealingInter-critical annealing is simulated. The thermal profiles from this simulation are extracted and passed on to microscale to repeat the process chain. All the simulation softwares are integrated together to implement a multi-scale simulation, aiming towards ICME approach.

Deepu Mathew John, Hamidreza Farivar, Gerald Rothenbucher, Ranjeet Kumar, Pramod Zagade, Danish Khan, Aravind Babu, B. P. Gautham, Ralph Bernhardt, G. Phanikumar, Ulrich Prahl

Integrated Microstructure Based Modelling of Process-Chain for Cold Rolled Dual Phase Steels

The properties of dual phase (DP) steels are governed by the underlying microstructure, the evolution of which is determined by the processing route. In order to design a dual phase steel with tailored properties, it is therefore important to model and design each of the process involved at the microstructure level in an integrated fashion. In this work, an integrated approach is used to predict the final microstructure and mechanical properties of dual phase steels through microstructure based modelling of cold rolling, intercritical annealing and quenching processes. Starting with a representative volume element (RVE) of initial ferrite-pearlite microstructure, cold-reduction during rolling is simulated in a FEM based micromechanics approach under appropriate boundary conditions. The deformed microstructure with plastic strain energy distribution after cold-reduction serves as input for modelling static recrystallization and ferrite/pearlite to austenite transformation during intercritical annealing using a phase-field approach. A micromechanics based quenching simulation is then used to model austenite to martensite transformation, related volume expansion and evolution of transformational stress/strain fields. The resultant microstructure with its complete state is used to evaluate the flow behavior under uniaxial loading conditions in a FEM based micromechanics approach under periodic boundary conditions. Property variation for different initial microstructure, composition and processing conditions are studied and discussed.

Danish Khan, Ayush Suhane, P. Srimannarayana, Akash Bhattacharjee, Gerald Tennyson, Pramod Zagade, B. P. Gautham

Improving Manufacturing Quality Using Integrated Computational Materials Engineering

The prediction of materials properties and their variation within a specification or design space is key in ensuring reliable production uniformity. To capture the complex mechanisms that underpin materials’ performance, processing-structure-properties links are established using a “systems design” approach. QuesTek Innovations LLC has previously utilized multi-scale ICME modeling methodologies and tools (e.g., CALPHAD thermodynamic and kinetic databases, property models, etc.) and advanced characterization techniques to design advanced materials with improved performance. This work focuses on building an ICME infrastructure to predictively model properties of critical materials for energy and defense applications by optimizing existing materials, performing calculations to quantify uncertainty in material properties, and defining target specification ranges and processing parameters necessary to ensure design allowables. Focusing on two material case studies, 304L austenitic stainless steel and glass-ceramic-to-metal seals, we show how these ICME techniques can be used to better understand process-structure and structure-property relationships. These efforts provide pathways to novel, fully optimized alloys and production processes using the Accelerated Insertion of Materials (AIM) methodology within ICME. The AIM method is used for probabilistic properties forecasting to enable rapid and cost-efficient process optimization and material qualification.

Dana Frankel, Nicholas Hatcher, David Snyder, Jason Sebastian, Gregory B. Olson, Greg Vernon, Wes Everhart, Lance Carroll

ICME Based Hierarchical Design Using Composite Materials for Automotive Structures

Composite materials are increasingly being used in transport structures due to their higher specific stiffness and specific strength. They can also be molded relatively easily to achieve aerodynamic shapes. Fiber reinforced composites offer excellent energy absorption under crushing loads and hence are increasingly being used in safety and load bearing applications. CompositeComposite material characterization is a complicated task due to micro-scale non-homogeneity and its resulting anisotropy and is generally accomplished with expensive physical tests at coupon level. High fidelity computational models are increasingly being used to accurately establish the elastic as well as inelastic nonlinear behaviour due micro-damage and fracture. The fiber material and its architecture, resin selection and its curing process control the resulting composite properties. Draping of fabrics before resin infusion also leads to geometrical non-linearities in the structure. All these parameters in the above processes need to be tightly coupled and can be altered in turn to provide a maximum performance for a given application under certain loads. A multi-scale methodology to study global-local relations of materials can also be integrated in the entire process. In this paper, Integrated Computational Materials Engineering based hierarchical design process integrated with composite material selection and microstructure based material design is presented. This framework for design decisions is currently being integrated using a TCS PREMɅP framework developed in house.

Azeez Shaik, Yagnik Kalariya, Rizwan Pathan, Amit Salvi

Towards Bridging the Data Exchange Gap Between Atomistic Simulation and Larger Scale Models

Materials properties are rooted in the atomic scale. Thus, an atomistic understanding of the physics and chemistry is the foundation of computational materials engineering. The MedeA computational environment provides a highly efficient platform for atomistic simulations to predict materials properties from the fundamental interactions effective at the nanoscale. Nevertheless, many interactions and processes occur at much larger time and length scales, that need to be described with microscale and macroscale models, as exemplified by the multiphase field tool MICRESS. The predictive power of these larger scale models can be greatly increased by augmenting them with atomistic simulation data. The notion of per phase-properties including their anisotropies provides e.g., the key for the determination of effective properties of multiphase materials. The key goal of the present work is to generate a common interface between atomistic and larger scale models using a data centric approach, in which the “interface” is provided by means of a standardized data structure based on the hierarchical data format HDF5HDF5. The example HDF5 file created by Schmitz et al., Sci. Technol. Adv. Mater. 17 (2016) 411, describing a three phase Al--Cu microstructure, is taken and extended to include atomistic simulation data of the Al--Cu phases, e.g., heats of formation, elastic properties, interfacial energies etc. This is pursued with special attention on using metadataMetadata to increase transparency and reproducibility of the data provided by the atomistic simulation tool MedeA.

David Reith, Mikael Christensen, Walter Wolf, Erich Wimmer, Georg J. Schmitz

A Flowchart Scheme for Information Retrieval in ICME Settings

Retrieving desired information about a specific material may either proceed via querying existing data, such as the general Internet or, if the desired information already exists, specifically dedicated databases. If the desired information is not yet available, it has to be determined by employing one or multiple models to compute the data. If multiple models are required for generating the desired information, interoperability between the models plays a vital role. Interoperability between models implies the need to define a flow of information or a “workflow” and also to specify the timing between the different operations of the different models acting on a state or on subsets of a state description. Ultimately getting such workflows well-defined, operational and also extendable to future decision making processes requires taking some structural considerations into account. An instructive approach is seen in the specification of workflows for decision making in different areas where different types of flowchart tools are needed and used to control and guide the workflow. The proposed flowchart scenario is based on the description of a system state whose evolution is influenced by distinct types of phenomena occurring at different scales. The system state further defines the properties which can be extracted from the system state information. Different types of models/tools operate on this state and a generic classification is proposed which is based on the character/functionality of physical equations, such as (i) evolution equations, (ii) property equations, (iii) equilibrium equations, and (iv) conservation equations.

Georg J. Schmitz

An Ontological Framework for Integrated Computational Materials Engineering

ICME is expected to significantly reduce the dependence on trial and error based experimentation cycles for materials development and deployment in products. However, modeling and simulation is a knowledge intensive activity. In an integrated design, choosing right models for different phenomena, at right scales, with right parameters, and ensuring integration across these models is a non-trivial task. The gaps in modeling and simulation need to be filled with tacit knowledge and co-engineered with product knowledge. Therefore, an IT platform having capabilities such as, (a) a repository of building-block models, templates and workflows with an intelligent means to choose and compose right workflows for a given problem, (b) a knowledge engineering framework for knowledge management, (c) a simulation services framework for simulation tool integration and simulation execution, (d) tools for decision support, optimization, robust design etc., is essential for scaling up ICME for industrial applicability. This requires a unifying semantic foundation. Ontologies can provide the common substrate for integration of different models, the common language for information exchange, and the means for capturing and organizing knowledge. However, ontology engineering is a challenge when we consider the diversity of the material systems, products, processes and mechanisms involved in ICME. This calls for a flexible ontological framework that provides a means for modeling the generic structure of a subject area (e.g. materials) and a means for instantiating subject specific ontologies from this generic structure. We describe a model driven framework and how it has been used for developing an enabling platform for ICME.

Sreedhar Reddy, B. P. Gautham, Prasenjit Das, Raghavendra Reddy Yeddula, Sushant Vale, Chetan Malhotra

European Materials Modelling Council

The aim of the European Materials Modelling Council (EMMC) is to establish current and forward looking complementary activities necessary to bring the field of materials modellingMaterials modelling closer to the demands of manufacturers (both small and large enterprises) in Europe. The ultimate goal is that materials modelling and simulation will become an integral part of product life cycle management in European industry, thereby making a strong contribution to enhance innovation and competitiveness on a global level. Based on intensive efforts in the past two years within the EMMC, which included numerous consultation and networking actions with representatives of all stakeholders including Modellers, Software Owners, Translators and Manufacturers in Europe, the EMMC identified and proposed a set of underpinning and enabling actions to increase the industrial exploitation of materials modelling in Europe. EMMC will pursue the following overarching objectives in order to bridge the gap between academic innovation and industrial application:enhance the interaction and collaboration between all stakeholders engaged in different types of materials modelling, including modellers, software owners, translators and manufacturers,facilitate integrated materials modellingMaterials modelling in Europe building on strong and coherent foundations,coordinate and support actors and mechanisms that enable rapid transfer of materials modelling from academic innovation to the end users and potential beneficiaries in industry,achieve greater awareness and uptake of materials modelling in industry, in particular SMEs,elaborate Roadmaps that (i) identify major obstacles to widening the use of materials modelling and (ii) elaborate strategies to overcome them.

Nadja Adamovic, Pietro Asinari, Gerhard Goldbeck, Adham Hashibon, Kersti Hermansson, Denka Hristova-Bogaerds, Rudolf Koopmans, Tom Verbrugge, Erich Wimmer

Facilitating ICME Through Platformization

Integrated Computational Materials Engineering (ICME)Integrated Computational Materials Engineering (ICME) is poised to be integral to the engineering design processes in the future where product engineering will be carried out in close association with materials and manufacturing engineering. This is already being manifested in newer technologies such as additive manufacturing and composite materials where the boundaries between product and process and material are sufficiently blurred. In order to successfully leverage ICME, we need enabling platforms that should allow for seamless integration of product design with process design and materials design and should allow for all three to be investigated, analyzed and optimized simultaneously to be able to obtain the right material for the right product to be manufactured in the right way. It should also provide for a unified and flexible language for expressing the problem domain and allow for the integration of modeling and simulation tools, product and materials databases as well as machine learning, data-analysis and optimization algorithms into the design process. Most importantly, such a platform should be context aware and knowledge enriched. It should provide a strong semantic basis for expressing and capturing knowledge related to the problem domain and a means to reason with this knowledge in a context-sensitive manner to provide context-appropriate guidance to the designer during the design process. The current paper proposes a basic structure for such a platform and how it is being realized as TCS-PREMAP.

B. P. Gautham, Sreedhar Reddy, Prasenjit Das, Chetan Malhotra

Bridging the Gap Between Bulk Properties and Confined Behavior Using Finite Element Analysis

Theoretically and empirically based models of materials properties are crucial tools in development of new materials; however, these models are often restricted to certain systems due to assumptions or fitting parameters. When expanding a model into alternative systems it is therefore necessary to have sufficient experimental data. When working with composite or highly confined materials, such as layered structures or coatings, this can be problematic as most available data is on bulk materials. The present work displays the potential of using Finite Element Method (FEM) simulations as a tool to understand experimental observations and expand existing models to new systems using only bulk properties of the constituent phases. The present work focuses on the effect of geometrical constraints on the indentation behaviorIndentation behavior of elasto-plastic materials as an example on how FEM may be used to better understand experimental observations in composite or layered materials. The results may also be integrated into phenomenological models, expanding their application range.

David Linder, John Ågren, Annika Borgenstam

Ontology Dedicated to Knowledge-Driven Optimization for ICME Approach

Development of new materials, products and technologies with the ICME approach requires challenging computations, controlled by optimization algorithms. A computational time might be decreased with a “knowledge-driven optimization”—an optimization process is controlled not only by a numerical algorithm, but also by a Knowledge Based System. That requires development of a common language, able to cover communication between numerical models without sophisticated translators. There are several formalisms of knowledge representation, but the most common ones are based on First Order Logic (FOL) and Description Logic (DL). None of them meets all the requirements of knowledge management in ICME processes. We present an approach to development of an environment for knowledge management, combining DL and FOL. An exemplary multiscale problem is described, as well as an OWL2 based ontology and rules controlling an optimization process.

Piotr Macioł, Andrzej Macioł, Łukasz Rauch

Integration of Experiments and Simulations to Build Material Big-Data

In this paper, a method for extracting stress-strain databases from material test measurements is introduced as one of the potential Integrated Computational Materials Engineering (ICME) tools. Measuring spatially heterogeneous stress and strain evolutionary data during material tests is a challenging and costly task. The proposed method can extract a large volume of spatially heterogeneous stress and strain evolutionary data from experimental boundary measurements such as tractions and displacements. For the purpose, nonlinear finite element models are intrusively implemented with artificial neural network (ANN)-based material constitutive models. Then a specialized algorithm that can auto-progressively train ANN material models guided by experimental measurements is executed. Any complex constitutive law is not presumed. From the algorithm, ANN gradually learns complex material constitutive behavior. The training databases are gradually accumulated with self-corrected stress and strain data predicted by the ANN. Finally, material databases are obtained. For an example, visco-elastoplastic material databases are obtained by the proposed method.

Gun Jin Yun

ICME Design Tools and Application


ICME-Based Process and Alloy Design for Vacuum Carburized Steel Components with High Potential of Reduced Distortion

Carburized steel components are usually quenched from a hardening temperature, which lies in a complete austenitic phase, to room temperature. This leads to a microstructure comprised of mostly martensite plus bainite giving rise to unwanted heat-treatment-induced distortion. However, having a soft phase of ferrite dispersed throughout the microstructure can be quite effective in this regard. This is attributed to the capability of ferrite in accommodating the plasticity resulted from austenite-to-martensite transformation expansion. In the context of this work, it is demonstrated that how a proper selection of chemical compositions and a hardening temperature can greatly suppress the associated distortionDistortion. Hence, in order to systematically design a new steel alloy which fits to the above mentioned conditions, an ICMEICME-based methodology has been employed. Thus, a series of calculations have been carried out by means of the well-known thermodynamic-based software Thermo-Calc® and the scripting language of Python. The austenite to ferrite phase transformation kinetics is also captured by the software DICTRA® generating a virtual TTT (Time-Temperature-Transformation) diagram which is subsequently utilized for further finite element simulationsSimulation in the software Simufact.forming®. The carburizing processCarburizing process, the following phase transformations and the effect of the developed microstructure on the final distortion are simulated in macro-scale through Simufact.forming. The finite-element-based results of the Simufact.forming have in turn been enhanced by the results of the above-mentioned thermodynamic-based computational tools. At a later stage the simulation outcomes are experimentally validated by employing Navy C-Ring specimens.

H. Farivar, G. Rothenbucher, U. Prahl, R. Bernhardt

Study of Transient Behavior of Slag Layer in Bottom Purged Ladle: A CFD Approach

Purging of argon gas in the molten metal bath is a process that is regularly involved in secondary steel making operations. The injected gas imparts momentum to the liquid metal, which induces high turbulence in the molten metal and helps in homogenization of the bath composition and temperature, and facilitates the slag metal interactions. In this study, a computational fluid dynamics (CFD) based numerical investigation is carried out on an argon gas stirred ladle to study the flow and interface behavior in a secondary steel making ladleSteel making ladle. A transient, three phase coupled level-set volume of fluid (CLSVOF) model is employed to track the slag-metal, gas-metal and slag-gas interfaces. The transient behavior of slag layer deformation and open eye formation is studied for different slag layer to metal bath height ratios at various argon gas flow rates.

Vishnu Teja Mantripragada, Sabita Sarkar

Developing Cemented Carbides Through ICME

The ICME (Integrated Computational Materials Engineering) for cemented carbides aims to combine key experiments with multi-scale simulations from nano (10−10~10−8 m) to micro (10−8~10−4 m) to meso (10−4~10−2 m) and to macro (10−2~10 m) during the whole R&D process of cemented carbides. Based on ICME, the framework for R&D of cemented carbides, involving end-user demand, product design and industrial application, is established. In this work, a description to our established thermodynamic and thermophysical (diffusion coefficient, interfacial energy, and thermal conductivity and so on) databases is presented, followed by simulation of microstructure evolution during sintering of cemented carbides by means of phase field method. Work is also done to investigate the correlation between microstructure and mechanical properties (crack, stress distribution, and coupled temp-displacement) by using phase field and finite element methods. The proposed ICME for cemented carbides is used to develop a few new cemented carbides (including double layer gradient cemented carbides and γ′-strengthened Co–Ni–Al binder cemented carbides), which have found industry applications.

Yong Du, Yingbiao Peng, Peng Zhou, Yafei Pan, Weibin Zhang, Cong Zhang, Kaiming Cheng, Kai Li, Han Li, Haixia Tian, Yue Qiu, Peng Deng, Na Li, Chong Chen, Yaru Wang, Yi Kong, Li Chen, Jianzhan Long, Wen Xie, Guanghua Wen, Shequan Wang, Zhongjian Zhang, Tao Xu

CSUDDCC2: An Updated Diffusion Database for Cemented Carbides

Cemented carbides are widely used in industry as cutting tools, wear parts, as a result of the high hardness and good toughness. A reliable diffusion database is critical to simulate microstructure evolution of cemented carbides. In 2014, we established version one of CSUDDCC1 (Central South University Diffusion Database for Cemented Carbides Version one). In this work, a description for the updated diffusion databaseDiffusion database CSUDDCC2 is presented. The atomic mobility database for fcc and liquid in C–W–Co–Fe–Ni–Cr–V–Ti–Ta–Nb–Zr–Mo–Al–N cemented carbides was established based on our new experimental data, literature data, first-principles calculation and theoretical assessment via the DICTRA (Diffusion Controlled TRAnsformation) software package. The atomic mobility parameters in liquid are theoretically calculated by the newly modified Sutherland equation, and the atomic mobilityAtomic mobility parameters in fcc phase are optimized by the diffusivities measured in the present work and from the literature. The mobility parameters for self-diffusion and impurity diffusion in metastable fcc structure were determined through a semi-empirical method or first-principles calculations. Comprehensive comparisons between calculated and measured diffusivities indicate that most of the experimental data can be well reproduced by the currently obtained atomic mobilities. Combining the thermodynamic database for cemented carbidesCemented carbides, the diffusion database has been used to simulate the microstructure evolution during sintering of gradient cemented carbides. The simulated microstructure agrees reasonably with the experimentally observations.

Peng Deng, Yong Du, Weibin Zhang, Cong Chen, Cong Zhang, Jinfeng Zhang, Yingbiao Peng, Peng Zhou, Weimin Chen

Microstructure Evolution


Multi-scale Modeling of Quasi-directional Solidification of a Cast Si-Rich Eutectic Alloy

Dow Corning Corporation recently examined the use of transition metal-silicon eutectics for producing melt-castable ceramic parts. These materials display good strength, wear and corrosion resistance. The near-eutectic solidificationSolidification structure has significant impact on the final properties of a cast component. However, direct simulation of the cast structure at industrial scales remains a challenge. The objective of this work is to develop a multi-scale integrated solidification model that includes: density functional theory (DFT) calculations, which enable the computation of difficult-to-measure thermophysical properties; microstructural evolution simulation, which tackles nucleation eutecticEutectic growth and segregation during solidification; and casting modeling, which accounts for different boundary conditions including temperature-dependent heat transfer coefficients and geometry. The developed 3D coupled code can predict the correct morphology of the solidified composite and aid in the design and optimization of melt-cast parts based on composition and process parameters in a virtual environment. To verify the model, a mold was designed to achieve quasi-directional solidification within large regions of each casting; hypo- and hyper-eutecticEutectic Si–Cr alloys were cast into this custom mold using a vacuum tilt pour unit. Our experimental efforts focused on the quantification of the effects of process conditions on the resulting microstructure of the cast component. Local segregation was examined and compared with the model’s predictions. Results are in agreement with the microstructure observed in our castings.

Chang Kai Wu, Kwan Skinner, Andres E. Becerra, Vasgen A. Shamamian, Salem Mosbah

Numerical Simulation of Macrosegregation in a 535 Tons Steel Ingot with a Multicomponent-Multiphase Model

To accurately simulate the formation of macrosegregation, a major defect commonly encountered in large ingots, solidification researchers have developed various mathematical models and conducted corresponding steel ingotSteel ingots dissection experiments for validation. A multicomponentMulticomponent and multiphase solidification model was utilized to predict macrosegregationMacrosegregation of steel ingots in this research. The model described the multi-phase flow phenomenon during solidification, with the feature of strong coupling among mass, momentum, energy, and species conservation equations. Impact factors as thermo-solutal buoyancy flow, grains sedimentation, and shrinkage-induced flow on the macroscopic scale were taken into consideration. Additionally, the interfacial concentration constraint relations were derived to close the model by solving the solidification paths in the multicomponent alloy system. A finite-volume method was employed to solve the governing equations of the model. In particular, a multi-phase SIMPLEC (semi-implicit method for pressure-linked equations-consistent) algorithm was utilized to solve the velocity-pressure coupling for the specific multiphase flow system. Finally, the model was applied to simulate the macrosegregation in a 535 tons steel ingot. The simulated results were compared with the experimental results and the predictions reproduced the classical macrosegregation patterns. Good agreement is shown generally in quantitative comparisons between experimental results and numerical predictions of carbon, chromium and molybdenum concentration. It is demonstrated that the multicomponent-multiphase solidification model can well predict macrosegregation in steel ingots and help optimize the ingot production process.

Kangxin Chen, Wutao Tu, Houfa Shen

Validation of CAFE Model with Experimental Macroscopic Grain Structures in a 36-Ton Steel Ingot

In order to recognize macroscopic grain structuresMacroscopic grain structures evolution within large heavy casting, a 36-ton steel ingotSteel ingot has been experimentally investigated. Thirteen thermocouples have been used to record temperature variations during solidification of the ingot to ensure a reliable simulationSimulation of temperature field. Half of the ingot tail in the longitudinal section has been etched to obtain as-cast macrostructure. Fine equiaxed grains are found in the ingot tail periphery, then slender columnar grains next to them, finally widely spread coarse equiaxed grains in the ingot tail center. Then, simulation of macroscopic grain structure is processed by a three dimensional Cellular Automaton Finite Element (CAFE)Cellular Automaton Finite Element (CAFE) module of ProCAST software. The nucleation algorithm is based on an instantaneous nucleation model considering a Gaussian distribution of nucleation sites proposed by Rappaz. The growth algorithm is based on the growth of an octahedron bounded by (111) faces and the growth kinetics law is given by the model of Kurz et al. The microscopic CA and macroscopic FE calculation are coupled where the temperature of each cell is simply interpolated from the temperature of the FE nodes using a unique solidification path at the macroscopic scale. Simulation parameters of CAFE about Gaussian nucleation and growth kinetics have been adjusted so that the macroscopic grain structures correlate with the as-cast macrostructure experiment.

Jing’an Yang, Zhenhu Duan, Houfa Shen, Baicheng Liu

Analysis of Localized Plastic Strain in Heterogeneous Cast Iron Microstructures Using 3D Finite Element Simulations

The design and production of light structures in cast iron with high static and fatigue performance is of major interest in e.g. the automotive area. Since the casting process inevitably leads to heterogeneous solidification conditions and variations in microstructural features and material properties, the effects on multiple scale levels needs to be considered in the determination of the local fatigue performance. In the current work, microstructural features of different cast ironsCast iron are captured by use of micro X-ray tomographyX-ray tomography, and 3D finite element models generated. The details of the 3D microstructureMicrostructure differ from the commonly used 2D representations in that the actual geometry is captured and that there is not a need to compensate for 3D-effects. The first objective with the present study is to try and highlight certain aspects at the micro scale that might be the underlying cause of fatigue crack initiation, and ultimately crack propagation, under fatigue loading for cast iron alloys. The second objective is to incorporate the gained knowledge about the microstructural behavior into multi-scale simulations at a structural length scale, including the local damage level obtained in the heterogeneous structure subjected to fatigue load.

Kent Salomonsson, Jakob Olofsson

An Integrated Solidification and Heat Treatment Model for Predicting Mechanical Properties of Cast Aluminum Alloy Component

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 solidificationSolidification 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.

Chang Kai Wu, Salem Mosbah

Linked Heat Treatment and Bending Simulation of Aluminium Tailored Heat Treated Profiles

Precipitation hardening aluminium alloys enable tailoring of mechanical properties through the dissolution of strength-increasing precipitates during a local short-term heat treatment. Tailor Heat Treated Profiles (THTP) are aluminium extrusion profiles with locally different material properties, specifically optimised for succeeding bending processes. Softened areas need to be generated next to hardened areas to optimise the material flow during the forming process. To determine the optimised 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 modelling 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 behaviour during heating and cooling of aluminium profiles 6060 T4 is investigated using differential scanning calorimetry. Thermo-mechanical analysis is applied for evaluation of the mechanical properties. This behaviour 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.

Hannes Fröck, Matthias Graser, Michael Reich, Michael Lechner, Marion Merklein, Olaf Kessler

Numerical Simulation of Meso-Micro Structure in Ni-Based Superalloy During Liquid Metal Cooling Process

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 simulationNumerical 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.

Xuewei Yan, Wei Li, Lei Yao, Xin Xue, Yanbin Wang, Gang Zhao, Juntao Li, Qingyan Xu, Baicheng Liu

Phase Field Modeling


Multiscale Simulation of α-Mg Dendrite Growth via 3D Phase Field Modeling and Ab Initio First Principle Calculations

Based on synchrotron X-ray tomography and electron backscattered diffraction techniques, recent studies revealed that the α-Mg dendrite exhibited an 18-primary-branch morphology in 3D, of which six grew along $$ < 11\overline{2}0 > $$ on the basal plane, whereas the other twelve along $$ < 11\overline{2}3 > $$ on non-basal planes. To describe this growth behaviour and simulate the morphology of the α-Mg dendrite in 3D, an anisotropy function based on cubic harmonics was developed and coupled into a 3D phase field model previously developed by the current authors. Results showed that this anisotropy function, together with the phase field model could perfectly describe the 18-primary-branch dendrite morphology for the magnesium alloys. The growth tendency or orientation selection of the 18-primary-branch morphology was further investigated by performing ab initio first principle calculations based on the hexagonal symmetry structure. It was showed that those crystallographic planes normal to the preferred growth directions of α-Mg dendrite were characterized by higher surface energy than these of others, i.e. coinciding with the 18-primary-branch dendritic morphology. Apart from agreement with experiment results and providing great insights in understanding dendrite growth behaviour, such multiscale computing scheme could also be employed as a standard tool for studying general pattern formation behaviours in solidification.

Jinglian Du, Zhipeng Guo, Manhong Yang, Shoumei Xiong

Macro- and Micro-Simulation and Experiment Study on Microstructure and Mechanical Properties of Squeeze Casting Wheel of Magnesium Alloy

The macro- and micro-simulationMacro- and Micro-simulation based on a coupled thermo-mechanical simulation method using ANSYS® and phase fieldPhase field modeling with pressure effects were carried out for squeeze casting wheel of AT72 alloy. The mechanical properties at different positions of the wheel and under different pressures were analyzed by the macro- and micro-simulation and experimental results, and the corresponding strengthening mechanismStrengthening mechanism was discussed. Firstly, the mechanical properties in spoke are better than those in rim due to higher integrity associated with more forced feeding including more liquid flow feeding and almost all of the plastic deformation feeding in spoke. Furthermore, the mechanical properties increase with pressure due to the enhanced forced feeding shown by the macro-simulation results and the more developed dendrite arms, finer dendrites and more solutes in dendrites under higher pressure indicated by the micro-simulation and experimental results. As analyzed, the mechanical properties are improved by applied pressure according to the strengthening mechanismStrengthening mechanism, including strengthening associated with high integrity, fine-grain strengthening and solution strengthening.

Shan Shang, Bin Hu, Zhiqiang Han, Weihua Sun, Alan A. Luo

Solidification Simulation of Fe–Cr–Ni–Mo–C Duplex Stainless Steel Using CALPHAD-Coupled Multi-phase Field Model with Finite Interface Dissipation

A multi-phase field (MPF) modelMulti-phase field model with finite interface dissipation proposed by Steinbach et al. is applied to simulate the dendritic solidificationSolidification in Fe–Cr–Ni–Mo–C duplex stainless steelStainless steel. This MPF model does not require an equal diffusion potential assumption and can take into account a substantial non-equilibrium interfacial condition. We develop the MPF code to couple with the CALPHADCALPHAD thermodynamic database to simulate two-dimensional microstructure evolutions in multi-component alloys using the TQ-interface of Thermo-Calc. The message passing interface parallelization technique is adapted to the program code development to reduce computational elapse time. Solidification calculations were performed in two cases of quinary compositions: Fe–16Cr–2Mo–10Ni–0.08C and Fe–17Cr–2Mo–9Ni–0.08C. We confirm that the developed MPF method can be highly applicable to microstructure evolution simulation of the engineering metal alloy solidification.

Sukeharu Nomoto, Kazuki Mori, Masahito Segawa, Akinori Yamanaka

Phase-Field Modeling of θ′ Precipitation Kinetics in W319 Alloys

Understanding and predicting the morphology, kinetics and hardening effects of precipitates are critical in improving the mechanical properties of Al-Cu-based alloysAl-Cu-based alloys through controlling the temperature and duration of the heat treatment process. In this work, we present a comprehensive phase-field framework for simulating the kinetics of θ′ precipitates in W319 alloys, integrating the thermodynamic and diffusion mobility databases of the system, the key precipitate anisotropic energy contributions from literature and first-principles calculations, as well as a nucleation model based on the classical nucleation theory. By systematically performing phase-field simulations, assuming the precipitate peak number densities determined from experiments, we optimize the model parameters to obtain the best possible match to the average diameters, thicknesses and volume fractions of precipitates from experimental measurements at 190, 230 and 260 °C. With these parameters available, the phase-field simulations can be performed at other aging temperatures. The possible extensions of the current phase-field modelPhase-field model for more accurate prediction of the precipitate behaviors in W319 alloys will also be discussed.

Yanzhou Ji, Bita Ghaffari, Mei Li, Long-Qing Chen

Mechanical Performance Using Multi-scale Modeling


Hybrid Hierarchical Model for Damage and Fracture Analysis in Heterogeneous Material

Complex materials with heterogeneities and discontinuities is a focus of current research in materials science and engineering because such materials promise to have superior properties including enhanced mechanical strength and fatigue resistance. Predictive damage and fracture analysis of complex materials is grueling since it involves the modeling of highly-coupled nonlinear processes at disparate scales. A logical approach taken by many researchers in tackling this challenge is to employ a framework that couples Molecular Dynamic (MD) and Finite Element (FE) modeling in some manner to capture damage processes occurring at different time and length scales. Unfortunately, such coupling typically suffers from the lack of thermodynamic consistency between the MD and FE models and causes pathological wave reflection that commonly occurs at the interface between the MD and FE simulation regions. This work endeavors to circumvent those problems by introducing a Hybrid Hierarchical Model (HHM) that consists of an MD module with an ab initio based force field and a peridynamic continuum mesoscale module. The HHM framework was applied to perform the fracture modeling of a silicon carbide slab with pre-crack and the high-cycle fatigue damage analysis of a turbine blade.

Alex V. Vasenkov

Fatigue Performance Prediction of Structural Materials by Multi-scale Modeling and Machine Learning

Structural materials having higher performance in strength, toughness, and fatigue resistance are strongly required. In the conventional materials development, many fatigue tests need to be conducted to validate statistical behavior of fatigue failure. Accordingly the evaluation of fatigue properties with shorter time becomes quite essential. Based on such background, we are developing fatigue prediction methods for wide range of structural materials by multi-scale finite element analysis (FEA)Multi-scale finite element method and machine learning in the Materials Integration (MI)Materials integration system. The multi-scale FEA consists of the following procedures: (i) mechanical and thermal properties are estimated by using commercially available software and database; (ii) temperature field, residual stress and distortion generated during a manufacturing process is calculated on the macroscopic model by thermo-mechanical FEA; (iii) macroscopic stress field under cyclic loading condition is calculated with a hardening constitutive model; (iv) the microscopic stress field is derived by finite element model with the polycrystalline structures and the cycles for a fatigue crack initiation is analyzed by strain energy accumulation on the slip plane; (v) the cycles for fatigue crack propagation is analyzed by extended finite element method (X-FEM) and the total number of cycles to the failure is obtained. The second approach is to use machine learning techniques to obtain empirical prediction formula. The database was prepared from published resources and experiments. Deterministic machine learning techniques such as multivariate linear regression and artificial neural network provided accurate equations to predict fatigue strength from materials and process parameters. Additionally, the concept of model-based machine learningModel-based machine learning was adopted to incorporate prior knowledge of microstructures and properties, and to account for uncertainty on fatigue life. The results showed that model-based machine learning was a promising tool for predicting fatigue performance in structural materials. The features and limitations of our prediction methods will be discussed.

Takayuki Shiraiwa, Fabien Briffod, Yuto Miyazawa, Manabu Enoki

Nano Simulation Study of Mechanical Property Parameter for Microstructure-Based Multiscale Simulation

We proposed a microstructure-based multiscale simulationMicrostructure-based multiscale simulation of duplex stainless steelDuplex stainless steel by using the multi-phase field method and finite element method software. Use of an accurate elastic constant is the key to the success of these simulations. However, it is difficult to obtain the elastic constant for the each constituent phase in multicomponent steels from a database and datebook. Herein, the elastic constant of each constituent phase of duplex stainless steel (Fe–Cr–Ni alloy) was calculated by first-principles and molecular dynamics (MD) simulationMolecular dynamics simulation. The commercial software VASP was used to estimate the elastic constants of the bcc structure. On the other hand, the open-source MD software LAMMPS was used to estimate the elastic constants of the fcc structure. Calculations were performed using 10,000 models in which the Cr and Ni atoms were repositioned at random by MD simulation. The elastic constant volumes showed a Gaussian-like distribution, and this was explained using a radial distribution function. The calculated elastic constants C11, C12, and C44 were good agreement with experimental values.

K. Mori, M. Oba, S. Nomoto, A. Yamanaka

ICME Success Stories and Applications


Multiscale, Coupled Chemo-mechanical Modeling of Bainitic Transformation During Press Hardening

We present our recent developments in multiscale and multiphysics modeling of bainite formation under mechanical loads in the press hardening process. The full field description of the bainitic microstructure by a multi-phase field model is linked to a crystal plasticity model at micrometer scale to simulate the mutual interaction between the phase transformation and plastic accommodation of the lattice distortion. Homogenized parameters of the phase fields are then coupled with a finite element model at a larger length scale to facilitate the calculation of transformation plasticity. The crystallographic features, transformation strain and texture of the simulated phase structure are discussed with comparison with experimental observations.

Ulrich Prahl, Mingxuan Lin, Marc Weikamp, Claas Hueter, Diego Schicchi, Martin Hunkel, Robert Spatschek

Development of Microstructure-Based Multiscale Simulation Process for Hot Rolling of Duplex Stainless Steel

Recent improvement of multi-phase field method enables us to simulate microstructure formed by various material processes and homogenization methodHomogenization method attracts attention as the way of bridging microstructure and macro homogenized material properties. We have proposed microstructure-based multiscale simulation framework and it was applied to the simulation of hot rolling process of duplex stainless steel. In the framework various commercial software, not only multi-phase field methodMulti-phase field method and homogenizaiton method but also nanoscale molecular dynamicsMolecular dynamics simulation and finite element methodFinite element method was bridged. Multi-phase field method coupled with CALPHAD database was used to simulate microstructure evolution by columnar and equiaxed solidifications during continuous casting. Elastic property for the constituent phases in the duplex stainless steel was calculated by molecular dynamics simulation and first principles calculation. Plastic property was obtained by nano-indentation tests. Homogenization calculation gave macro elastic property from microstructure and property of each phase and virtual material test performed by finite element methodFinite element method served homogenized plastic property. With the material properties hot rolling process was simulated by dynamic explicit simulation of finite element method. Recrystallization by hot rolling process was performed by multi-phase field method. In this paper, the results are discussed to reveal the usefulness and problem for performing microstructure based multiscale analysisMultiscale analysis. Further discussion is given for the framework here: the method for obtaining material property of each micro phase, anisotropy of homogenized elastic constants, three-dimensional recrystallization calculation. Through these discussions, our simulation framework becomes more reliable.

Mototeru Oba, Sukeharu Nomoto, Kazuki Mori, Akinori Yamanaka

A Decision-Based Design Method to Explore the Solution Space for Microstructure After Cooling Stage to Realize the End Mechanical Properties of Hot Rolled Product

Manufacturing a product involves a host of unit operations and the end properties of the manufactured product depends on the processing steps carried out in each of these unit operations. In order to couple the material processing-structure-property-performance spaces, both systems-based materials design and multiscale modeling of unit operations are required followed by integration of these models at different length scales (vertical integration). This facilitates the flow of information from one unit operation to another thereby establishing the integration of manufacturing processes to realize the end product (horizontal integration). In this paper, we present a goal-oriented inverse, decision-based design method using the compromise Decision Support Problem construct to achieve the vertical and horizontal integration of models by identifying the design set points for hot rod rolling process chain. We illustrate the efficacy of the method by exploring the design space for the microstructure after cooling stage that satisfies the requirements identified for the end mechanical properties of a hot rolled product. Specific requirements like managing the banded microstructure to avoid distortion in forged gear blanks are considered for the problem. The method is goal-oriented as the design solutions after exploration of microstructure space are passed in an inverse manner to cooling and rolling stages to identify the design set points in order to realize the end product. The method is generic and has the potential to be used for exploring the design space of manufacturing stages that are connected to achieve the integrated decision-based design of the product and processes.

Anand Balu Nellippallil, Vignesh Rangaraj, Janet K. Allen, Farrokh Mistree, B. P. Gautham, Amarendra K. Singh

Influence of Computational Grid and Deposit Volume on Residual Stress and Distortion Prediction Accuracy for Additive Manufacturing Modeling

Powder Bed Additive Manufacturing offers unique advantages in terms of cost, lot size and manufacturability of complex products. The energy used however leads to distortions during the process. The distortion of single layers can be comparable with the powder layer thickness. The contact between the coater blade and the deposited material could terminate the build process. Furthermore, accumulated residual stresses can lead to deviations of the final shape from the design. This work focusses on the accuracy of quick residual stress and distortion models that will both provide layer by layer distortion data as well as the final work piece residual stress and shape. The residual stress and distortion models are implemented in an ICME platform that takes powder size distribution as well as the heat source powder interaction into account. Lower scale models are briefly introduced and data required for the residual stress analysis are documented prior to the analysis of some large components assessing manufacturability and final work piece shape.

O. Desmaison, P.-A. Pires, G. Levesque, A. Peralta, S. Sundarraj, A. Makinde, V. Jagdale, M. Megahed


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