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Computer Vision Approaches for Segmentation of Nanoscale Precipitates in Nickel-Based Superalloy IN718 Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-12-16 Nishan M. Senanayake, Jennifer L. W. Carter
Extracting accurate volume fraction and size measurements of γ″ and γ′ precipitates in iron-based superalloys from micrographs is challenging and conventionally involves manual image processing due to their smaller size, and similar crystal structures and chemistries. The co-precipitation of composite particles further complicates automated segmentation. In this work, different types of traditional
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Informing Mechanical Model Development Using Lower-Dimensional Descriptions of Lattice Distortion Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-12-11 Darren C. Pagan, Gideon H. Schmidt, Andy D. Borum, Timothy J. Long, Armand J. Beaudoin
This paper describes a method combining in situ X-ray diffraction data and dimensionality reduction (local linear embedding) to inform the development of state variable plasticity models. The method is applied to developing a state variable plasticity model for pure nickel deformed in uniaxial tension in the small strain regime. Prior to model development, connections between state variables representing
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Numerical Evaluation of Advanced Laser Control Strategies Influence on Residual Stresses for Laser Powder Bed Fusion Systems Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-11-30 Massimo Carraturo, Brandon Lane, Ho Yeung, Stefan Kollmannsberger, Alessandro Reali, Ferdinando Auricchio
Process-dependent residual stresses are one of the main burdens to a widespread adoption of laser powder bed fusion technology in industry. Residual stresses are directly influenced by process parameters, such as laser path, laser power, and speed. In this work, the influence of various scan speed and laser power control strategies on residual stresses is investigated. A set of nine different laser
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A New Numerical-Homogenization Method to Predict the Effective Permittivity of Composite Materials Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-11-23 Younes Jarmoumi, Abdelali Derouiche, Fatna Benzouine
The effective permittivity of composite materials depends highly on the geometry, the arrangement, and the permittivity of each component. This research proposes a new numerical method that takes into account those dependencies through assemblies of virtual capacitors (electrical circuit). Then, the effective permittivity is calculated from the equivalent capacity of the suggested circuits. The new
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Model-Based Feature Information Network (MFIN): A Digital Twin Framework to Integrate Location-Specific Material Behavior Within Component Design, Manufacturing, and Performance Analysis Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-11-19 Saikiran Gopalakrishnan, Nathan W. Hartman, Michael D. Sangid
The digital transformation of manufacturing requires digitalization, including automatic and efficient data exchange. Model-based definitions (MBDs) capture digital product definitions, in order to eliminate error-prone information exchange associated with traditional paper-based drawings and to provide contextual information through additional metadata. The flow of MBDs extends throughout the product
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Effect of Particle Spreading Dynamics on Powder Bed Quality in Metal Additive Manufacturing Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-11-19 Yousub Lee, A. Kate Gurnon, David Bodner, Srdjan Simunovic
Powder spreading precedes creation of every new layer in powder bed additive manufacturing (AM). The powder spreading process can lead to powder layer defects such as porosity, poor surface roughness and particle segregation. Therefore, the creation of homogeneous layers is the first task for optimal part printing. Discrete element methods (DEM) powder spreading simulations are typically limited to
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Machine Learning-Enabled Uncertainty Quantification for Modeling Structure–Property Linkages for Fatigue Critical Engineering Alloys Using an ICME Workflow Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-11-18 Gary Whelan, David L. McDowell
Integrated computational materials engineering (ICME) facilitates efficient approaches to new material discovery and design, as well as optimization of existing materials. Computational models provide a way to rapidly screen candidate material designs such that materials can be tailored for specific applications in the product design cycle. Uncertainty is ubiquitous in ICME process–structure–property
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AMB2018-03: Benchmark Physical Property Measurements for Material Extrusion Additive Manufacturing of Polycarbonate Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-10-29 Daniel P. Cole, Frank Gardea, Todd C. Henry, Jonathan E. Seppala, Edward J. Garboczi, Kalman D. Migler, Christopher M. Shumeyko, Jeffrey R. Westrich, Sara V. Orski, Jeffrey L. Gair
Material extrusion (MatEx) is finding increasing applications in additive manufacturing of thermoplastics due to the ease of use and the ability to process disparate polymers. Since part strength is anisotropic and frequently deviates negatively with respect to parts produced by injection molding, an urgent challenge is to predict final properties of parts made through this method. A nascent effort
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Unsupervised Deep Learning for Laboratory-Based Diffraction Contrast Tomography Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-10-19 Emil Hovad, Haixing Fang, Yubin Zhang, Line Katrine Harder Clemmensen, Bjarne Kjær Ersbøll, Dorte Juul Jensen
An important leap forward for the 3D community is the possibility to perform non-destructive 3D microstructural imaging in the home laboratories. This possibility is profiled by a recently developed technique—laboratory X-ray diffraction contrast tomography (LabDCT). As diffraction spots in LabDCT images are the basis for 3D reconstruction of microstructures, it is critical to get their identification
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Data-Driven Constitutive Model for the Inelastic Response of Metals: Application to 316H Steel Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-10-02 Aaron E. Tallman, M. Arul Kumar, Andrew Castillo, Wei Wen, Laurent Capolungo, Carlos N. Tomé
Predictions of the mechanical response of structural elements are conditioned by the accuracy of constitutive models used at the engineering length-scale. In this regard, a prospect of mechanistic crystal-plasticity-based constitutive models is that they could be used for extrapolation beyond regimes in which they are calibrated. However, their use for assessing the performance of a component is computationally
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Uncertainty Quantified Parametrically Homogenized Constitutive Models for Microstructure-Integrated Structural Simulations Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-09-30 Shravan Kotha, Deniz Ozturk, Benjamin Smarslok, Somnath Ghosh
This paper investigates the role of material microstructures in structural analysis and establishes the need for microstructure-integrated constitutive models in predicting structural response. A focus is on microstructure and temperature dependency of stresses and plastic strains in a structural panel under realistic loading conditions. Structural analysis is conducted using the recently developed
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Model Selection and Evaluation for Machine Learning: Deep Learning in Materials Processing Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-09-14 Adam Kopper, Rasika Karkare, Randy C. Paffenroth, Diran Apelian
Materials processing is a critical subset of manufacturing which is benefitting by implementing machine learning to create knowledge from the data mined/collected and gain a deeper understanding of manufacturing processes. In this study, we focus on aluminum high-pressure die-casting (HPDC) process, which constitutes over 60% of all cast Al components. Routinely collected process data over a year’s
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An ICME Method for Predicting Phase Dissolution During Solution Treatment in Advanced Super Vacuum Die Cast Magnesium Alloys Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-09-14 Zhenjie Yao, Tracy Berman, John Allison
An integrated computational materials engineering (ICME) methodology was applied in this study to systematically and quantitatively study the second phase dissolution kinetics during the solution treatment process of a high pressure die cast magnesium sample. The study was conducted on Mg–9 wt% Al, Mg–5 wt% Al, and Mg–11 wt% Al binary alloys after isothermal solution treatments ranging from 380 to
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Temperature-Dependent Material Property Databases for Marine Steels—Part 1: DH36 Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-09-10 Daniel H. Bechetti, Jennifer K. Semple, Wei Zhang, Charles R. Fisher
Integrated computational materials engineering (ICME)-based tools and techniques have been identified as the best path forward for distortion mitigation in thin-plate steel construction at shipyards. ICME tools require temperature-dependent material properties to achieve accurate computational results for distortion and residual stress. However, the required temperature-dependent material property
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Mining the Correlations Between Optical Micrographs and Mechanical Properties of Cold-Rolled HSLA Steels Using Machine Learning Approaches Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-09-08 Berkay Yucel, Sezen Yucel, Arunim Ray, Lode Duprez, Surya R. Kalidindi
This paper demonstrates the feasibility of extracting quantitative linkages between optical micrographs and mechanical properties of cold-rolled HSLA (high-strength low alloy) steels measured in standardized tension tests. These linkages were established by bringing together modern toolsets for (i) image segmentation, (ii) rigorous statistical quantification of segmented microstructures, (iii) low-dimensional
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ICME Framework for Simulation of Microstructure and Property Evolution During Gas Metal Arc Welding in DP980 Steel Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-08-31 M. J. Deepu, G. Phanikumar
An integrated computational materials engineering (ICME)-based workflow was adopted for the study of microstructure and property evolution at the heat-affected zone (HAZ) of gas metal arc-welded DP980 steel. The macroscale simulation of the welding process was performed with finite element method (FEM) implemented in Simufact Welding® software and was experimentally validated. The time–temperature
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Is Domain Knowledge Necessary for Machine Learning Materials Properties? Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-08-27 Ryan J. Murdock, Steven K. Kauwe, Anthony Yu-Tung Wang, Taylor D. Sparks
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Extracting Knowledge from DFT: Experimental Band Gap Predictions Through Ensemble Learning Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-07-24 Steven K. Kauwe, Taylor Welker, Taylor D. Sparks
Many of the machine learning-based approaches for materials property predictions use low-cost computational data. The motivation for machine learning models is based on the orders of magnitude speedup compared to DFT calculations or experimental characterization. High-quality experimental materials data would be ideal for training these models; unfortunately, experimental data are typically costly
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Correction to: Universal Material Constants for MultiStage Fatigue (MSF) Modeling of the Process–Structure–Property (PSP) Relations of A000, 2000, 5000, and 7000 Series Aluminum Alloys Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-07-23 M. F. Horstemeyer, B. D. Huddleston, A. Bagheri, E. Carino, J. Hughes, Y. Mao, J. B. Jordon, S. Daniewicz, Cole Cauthen, Andrew Baker, Austin E. Mann, Steven Claves, Matt Watson
Readers should note the following error in this article.
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High-Throughput Exploration of the Process Space in 18% Ni (350) Maraging Steels via Spherical Indentation Stress–Strain Protocols and Gaussian Process Models Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-07-10 Sepideh Parvinian, Yuksel C. Yabansu, Ali Khosravani, Hamid Garmestani, Surya R. Kalidindi
Several challenges are encountered in the development of maraging steels with desired combinations of mechanical properties. These include the need to explore a large process design space, the time- and effort-consuming standardized testing protocols for property evaluations, and the lack of a formal design of experiments strategy that guides the selection of the process conditions for the next set
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Universal Material Constants for MultiStage Fatigue (MSF) Modeling of the Process–Structure–Property (PSP) Relations of A000, 2000, 5000, and 7000 Series Aluminum Alloys Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-06-22 M. F. Horstemeyer; B. D. Huddleston; A. Bagheri; E. Carino; J. Hughes; Y. Mao; J. B. Jordon; S. Daniewicz; Cole Cauthen; Andrew Baker; Austin E. Mann; Steven Clayes; Matt Watson
A MultiStage Fatigue (MSF) model that admits different hierarchical microstructural features and their stereological information is used to predict the fatigue behavior of 17 different processed aluminum alloys: A000 series (A319, A356, A357, and A380), 2000 series (2024, 2055, 2099, 2198, 2297), 5000 series (5052, 5456), and 7000 series (7050, 7055, 7065, 7075, 7085, 7175). A single set of MSF model
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Uncertainty Quantification Accounting for Model Discrepancy Within a Random Effects Bayesian Framework Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-06-22 Denielle E. Ricciardi; Oksana A. Chkrebtii; Stephen R. Niezgoda
With the advent of integrated computational materials engineering, there is a drive to exchange statistical confidence in a design obtained from repeated experimentation with one developed through modeling and simulation. Since these models are often missing physics or include incomplete knowledge or simplifying assumptions into their mathematical construct, they may not capture the physical system
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Benchmark AFLOW Data Sets for Machine Learning Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-05-27 Conrad L. Clement; Steven K. Kauwe; Taylor D. Sparks
Materials informatics is increasingly finding ways to exploit machine learning algorithms. Techniques such as decision trees, ensemble methods, support vector machines, and a variety of neural network architectures are used to predict likely material characteristics and property values. Supplemented with laboratory synthesis, applications of machine learning to compound discovery and characterization
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Location-Specific Microstructure Characterization Within IN625 Additive Manufacturing Benchmark Test Artifacts Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-03-03 M. R. Stoudt; M. E. Williams; L. E. Levine; A. Creuziger; S. A. Young; J. C. Heigel; B. M. Lane; T. Q. Phan
Additive manufacturing (AM) of alloys creates segregated microstructures with significant differences from those of traditional wrought alloys. Understanding how the local build conditions generate specific microstructures is essential for developing post-build heat treatments with the goal of producing parts with reliable and predictable properties. This research examines the position- and orientation-dependent
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Materials Abundance, Price, and Availability Data from the Years 1998 to 2015 Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-03-02 Brennan Theler; Steven K. Kauwe; Taylor D. Sparks
Materials researchers are paying ever more attention to sustainability, criticality, availability, and other industrial ecology metrics and concepts as they develop new materials. Previous reports for these metrics have typically been either for a few specific compositions or for a single year. In this work, we present a new curated dataset which reports the global elemental production on a per country
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In Situ Measurements of Melt-Pool Length and Cooling Rate During 3D Builds of the Metal AM-Bench Artifacts Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-02-20 Jarred C. Heigel; Brandon M. Lane; Lyle E. Levine
This work provides results and analysis of the in situ thermal measurement acquired during the 3D builds performed for the 2018 additive manufacturing benchmark tests. The objective is to provide context for post-process characterization of distortion, residual strain, and microstructure, which are reported elsewhere in this Journal, and to provide validation data for thermal models of the build process
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Correction to: PolyProc: A Modular Processing Pipeline for X-ray Diffraction Tomography Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-02-19 Jiwoong Kang, Ning Lu, Issac Loo, Nancy Senabulya, Ashwin J. Shahani
The article “PolyProc: A Modular Processing Pipeline for X-ray Diffraction Tomography” written by Jiwoong Kang, Ning Lu, Issac Loo, Nancy Senabulya, and Ashwin J. Shahani, was originally published Online First without Open Access.
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Outcomes and Conclusions from the 2018 AM-Bench Measurements, Challenge Problems, Modeling Submissions, and Conference Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-02-13 Lyle Levine; Brandon Lane; Jarred Heigel; Kalman Migler; Mark Stoudt; Thien Phan; Richard Ricker; Maria Strantza; Michael Hill; Fan Zhang; Jonathan Seppala; Edward Garboczi; Erich Bain; Daniel Cole; Andrew Allen; Jason Fox; Carelyn Campbell
The Additive Manufacturing Benchmark (AM-Bench) test series was established to provide rigorous measurement test data for validating additive manufacturing (AM) simulations for a broad range of AM technologies and material systems. AM-Bench includes extensive in situ and ex situ measurements, simulation challenges for the AM modeling community, and a corresponding conference series. In 2018, the first
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Measurements of Melt Pool Geometry and Cooling Rates of Individual Laser Traces on IN625 Bare Plates Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-02-05 Brandon Lane; Jarred Heigel; Richard Ricker; Ivan Zhirnov; Vladimir Khromschenko; Jordan Weaver; Thien Phan; Mark Stoudt; Sergey Mekhontsev; Lyle Levine
The complex physical nature of the laser powder bed fusion (LPBF) process warrants use of multiphysics computational simulations to predict or design optimal operating parameters or resultant part qualities such as microstructure or defect concentration. Many of these simulations rely on tuning based on characteristics of the laser-induced melt pool, such as the melt pool geometry (length, width, and
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Uncertainty Quantification and Propagation in Computational Materials Science and Simulation-Assisted Materials Design Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-01-23 Pejman Honarmandi; Raymundo Arróyave
Significant advances in theory, simulation tools, advanced computing infrastructure, and experimental frameworks have enabled the field of materials science to become increasingly reliant on computer simulations. Theory-grounded computational models provide a better understanding of observed materials phenomena. At the same time, computational tools constitute an important ingredient of any framework
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Data Assessment Method to Support the Development of Creep-Resistant Alloys Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-01-16 Madison Wenzlick; Jennifer R. Bauer; Kelly Rose; Jeffrey Hawk; Ram Devanathan
This work introduces a methodology to assess data quality for the tensile, creep/stress relaxation, and fatigue properties of alloys (as well as metadata associated with manufacture) as a part of a project to develop new materials for extreme environments. The extreme environments in question deal with those found in the power generation sector. Data quality assessment is needed to ensure the reliability
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A Framework for the Systematic Design of Segmentation Workflows Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2020-01-06 Almambet Iskakov; Surya R. Kalidindi
Segmentation of microscopy images is an essential step in most experimental studies of process–structure–property relationships in advanced materials. Currently employed segmentation approaches require the user to identify and string together a sequence of algorithms (and codes) into customized workflows that need extensive tweaking and optimization (often accomplished through repeated trials) for
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On the Origin of the Anisotropic Damage of X100 Line Pipe Steel: Part I—In Situ Synchrotron Tomography Experiments Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-12-02 Y. Madi; J.-M. Garcia; H. Proudhon; Y. Shinohara; L. Helfen; J. Besson; T. F. Morgeneyer
In this study, anisotropic ductility and associated damage mechanisms of a grade X100 line pipe steel previously studied at the macroscopic scale were investigated using in situ synchrotron radiation computed tomography of notched round bars. Line pipe materials have anisotropic mechanical properties, such as tensile strength, ductility and toughness. Specimens were tested for loading along both rolling
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Automatic Crack Detection and Analysis for Biological Cellular Materials in X-Ray In Situ Tomography Measurements Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-11-25 Ziling Wu; Ting Yang; Zhifei Deng; Baokun Huang; Han Liu; Yu Wang; Yuan Chen; Mary Caswell Stoddard; Ling Li; Yunhui Zhu
We introduce a novel methodology, based on in situ X-ray tomography measurements, to quantify and analyze 3D crack morphologies in biological cellular materials during damage process. Damage characterization in cellular materials is challenging due to the difficulty of identifying and registering cracks from the complicated 3D network structure. In this paper, we develop a pipeline of computer vision
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Study of Local Mechanical Responses in an Epoxy–Carbon Fiber Laminate Composite Using Spherical Indentation Stress–Strain Protocols Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-11-20 Alicia Rossi; Andrew Castillo; Craig Przybyla; Surya R. Kalidindi
Successful deployment of the highly heterogeneous, laminated, polymer matrix composites (PMCs) in high-performance structural applications is currently hindered by the lack of reliable experimental protocols for evaluation of the local mechanical responses at the salient meso-length/structure scales present in these material systems. Our main interest in this paper lies in establishing and demonstrating
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Estimation of Errors in Stress Distributions Computed in Finite Element Simulations of Polycrystals Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-11-18 Kamalika Chatterjee; Robert A. Carson; Paul R. Dawson
The accuracy of the stresses predicted from crystal plasticity-based finite element formulation depends on estimation and control of the errors associated with the discretization. In the current work, the errors in the stress distribution are estimated in virtual polycrystalline samples of α-phase titanium (hexagonal close-packed phase of Ti–6Al–4V). To estimate the error, the stress field, which does
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ModLayer: A MATLAB GUI Drawing Segmentation Tool for Visualizing and Classifying 3D Data Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-11-06 Imad Hanhan; Michael D. Sangid
Characterizing a material’s microstructure, especially as it relates to the manufacturing processes used to fabricate it, is of great interest to engineers and researchers. In recent years, state-of-the-art imaging techniques have been able to yield a plethora of high resolution 3D data that can be used to study materials at various length scales. This 3D data is usually organized as stacked serial
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ICME Framework for Damage Assessment and Remaining Creep Life Prediction of In-Service Turbine Blades Manufactured with Ni-Based Superalloys Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-11-04 Chao Fu; Yadong Chen; Siliang He; Stoichko Antonov; Longfei Li; Weiwei Zheng; Qiang Feng
Accurate creep life prediction is necessary for the evaluation of the remaining creep lives of in-service turbine blades and for the design of new turbine blades in aircraft engines. In this study, an integrated computational material engineering methodology for predicting the remaining creep life of in-service turbine blades was developed by taking a microstructural criterion and creep strain criterion
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Modeling Strain Localization in Microtextured Regions in a Titanium Alloy: Ti–6Al–4V Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-10-29 Kartik Kapoor; Ryan Noraas; Venkat Seetharaman; Michael D. Sangid
Large and highly textured regions, referred to as macrozones or microtextured regions, with sizes up to several orders of magnitude larger than those of the individual grains, are found in dual-phase titanium alloys as a consequence of the manufacturing process route. These macrozones have been shown to play a critical role in the failure of titanium alloys, specifically being linked to crack initiation
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Topographic Measurement of Individual Laser Tracks in Alloy 625 Bare Plates Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-10-10 Richard E. Ricker; Jarred C. Heigel; Brandon M. Lane; Ivan Zhirnov; Lyle E. Levine
Additive manufacturing (AM) combines all of the complexities of materials processing and manufacturing into a single process. The digital revolution made this combination possible, but the commercial viability of these technologies for critical parts may depend on digital process simulations to guide process development, product design, and part qualification. For laser powder bed fusion, one must
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Data Infrastructure Elements in Support of Accelerated Materials Innovation: ELA, PyMKS, and MATIN Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-10-10 Surya R. Kalidindi; Ali Khosravani; Berkay Yucel; Apaar Shanker; Aleksandr L. Blekh
Materials data management, analytics, and e-collaborations have been identified as three of the main technological gaps currently hindering the realization of the accelerated development and deployment of advanced materials targeted by the federal materials genome initiative. In this paper, we present our ongoing efforts aimed at addressing these critical gaps through the customized design and build
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Recent Tomographic Imaging Developments at the PSICHE Beamline Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-10-03 A. King; N. Guignot; J.-P. Deslandes; M. Pelerin; I. Joosten; D. De Looff; J. Li; L. Bertrand; E. Rosenberg; A. Dewaele; E. Boulard; Y. Le Godec; J.-P. Perrillat; E. Giovenco; G. Morard; T. Weitkamp; M. Scheel; J. Perrin; H. Chevreau; J.-P. Itié
PSICHE is a high-energy, multi-technique beamline at the SOLEIL synchrotron facility. It performs X-ray tomography for materials science and other applications and X-ray diffraction for samples at extreme conditions. The beamline has been in service for user experiments since 2013, but is in continual development to add new capabilities. In this article, we present a series of new developments which
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Uncertainty Quantification for Parameter Estimation and Response Prediction Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-09-06 Denielle E. Ricciardi; Oksana A. Chkrebtii; Stephen R. Niezgoda
Integrated Computational Materials Engineering (ICME) is an engineering approach where the materials, manufacturing process, and component designs are optimized concurrently before an actual physical component is realized. This requires the integration of models across vast length and timescales. A key benefit of ICME is the ability to reduce the bulk of expensive and lengthy experiments via tailored
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Statistical Characterization of Intragrain Misorientations at Large Strains Using High-Energy X-Ray Diffraction: Application to Hydrogen Embrittlement Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-09-04 Timothy J. H. Long; Matthew P. Miller
High-energy X-ray diffraction (HEXD) has become a powerful technique for studying deformation and failure in structural metals over the last two decades. In this work, we used multi-grain HEXD to investigate hydrogen embrittlement in polycrystalline nickel by quantifying the effects of solute hydrogen on the grain-scale plastic response. Five polycrystalline samples were probed: one undeformed control
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Correction to: A Tool to Generate Grain-Resolved Open-Cell Metal Foam Models Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-08-19 Joseph C. Tucker,Ashley D. Spear
Readers should note that this article was originally published without the electronic supplementary material with which it is now published.
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Sub-minute In Situ Fracture Test in a Laboratory CT Scanner Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-08-09 Clément Jailin; Amine Bouterf; Rafael Vargas; François Hild; Stéphane Roux
The present study aims at demonstrating the feasibility of performing a fracture test in less than 1 min in a laboratory CT scanner despite the severe time constraints of tomography acquisition. After introducing the basic concepts of projection-based digital volume correlation, the specific implementation of this methodology to a wedge splitting test on a refractory material is presented. The kinematics
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Three-Dimensional Characterization of Cracks in a Columnar Thermal Barrier Coating System for Gas Turbine Applications Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-08-07 Anne Dennstedt; Fabrice Gaslain; Marion Bartsch; Vincent Guipont; Vincent Maurel
Thermal barrier coatings (TBC) are multilayered systems comprising a metallic oxidation protection layer or so-called bond coat, a ceramic topcoat, and a thermally grown aluminum oxide developing at the interface. The coating systems fail typically by delamination cracking near this interface, which has a complex three-dimensional morphology influencing the crack path. This study combines laser shock
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Phase Fraction and Evolution of Additively Manufactured (AM) 15-5 Stainless Steel and Inconel 625 AM-Bench Artifacts Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-08-05 Fan Zhang; Lyle E. Levine; Andrew J. Allen; Sandra W. Young; Maureen E. Williams; Mark R. Stoudt; Kil-Won Moon; Jarred C. Heigel; Jan Ilavsky
A proper understanding of the structure and microstructure of additively manufactured (AM) alloys is essential not only to the prediction and assessment of their material properties, but also to the validation and verification of computer models needed to advance AM technologies. To accelerate AM development, as part of the AM-Bench effort, we conducted rigorous synchrotron-based X-ray scattering and
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AMB2018-04: Benchmark Physical Property Measurements for Powder Bed Fusion Additive Manufacturing of Polyamide 12 Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-08-05 Erich D. Bain; Edward J. Garboczi; Jonathan E. Seppala; Thomas C. Parker; Kalman B. Migler
Laser sintering (LS) of polyamide 12 (PA12) is increasingly being adopted for industrial production of end-use parts, yet the complexity of this process coupled with the lack of organized, rigorous, publicly available process-structure-physical property datasets exposes manufacturers and customers to risks of unacceptably poor part quality and high costs. Although an extensive scientific literature
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Elastic Residual Strain and Stress Measurements and Corresponding Part Deflections of 3D Additive Manufacturing Builds of IN625 AM-Bench Artifacts Using Neutron Diffraction, Synchrotron X-Ray Diffraction, and Contour Method Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-07-29 Thien Q. Phan; Maria Strantza; Michael R. Hill; Thomas H. Gnaupel-Herold; Jarred Heigel; Christopher R. D’Elia; Adrian T. DeWald; Bjorn Clausen; Darren C. Pagan; J. Y. Peter Ko; Donald W. Brown; Lyle E. Levine
One of the primary barriers for adoption of additive manufacturing (AM) has been the uncertainty in the performance of AM parts due to residual stresses/strains. The rapid heating and cooling rates from the thermal history of the laser melting process result in high residual stresses/strains that produce significant part distortion. Efforts to mitigate residual stresses using post-process heat treatments
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PolyProc: A Modular Processing Pipeline for X-ray Diffraction Tomography Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-07-18 Jiwoong Kang; Ning Lu; Issac Loo; Nancy Senabulya; Ashwin J. Shahani
Direct imaging of three-dimensional microstructure via X-ray diffraction-based techniques gives valuable insight into the crystallographic features that influence materials properties and performance. For instance, X-ray diffraction tomography provides information on grain orientation, position, size, and shape in a bulk specimen. As such techniques become more accessible to researchers, demands are
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Integrated Computational Materials Engineering to Predict Melt-Pool Dimensions and 3D Grain Structures for Selective Laser Melting of Inconel 625 Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-07-08 Jonathan Robichaud; Tim Vincent; Ben Schultheis; Anil Chaudhary
This work presents a comparison of simulation results with the experimental data for four of the six challenges within the National Institute of Standards and Technology (NIST) Additive Manufacturing (AM) Benchmark Test Series (AM Bench) problem AMB2018-02. This comparison is akin to a test case to assess the technology maturity level (TML) for the AM predictive capabilities that can be utilized to
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Residual Strain Predictions for a Powder Bed Fusion Inconel 625 Single Cantilever Part Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-07-03 Yangzhan Yang; Madie Allen; Tyler London; Victor Oancea
The laser powder bed fusion (LPBF) process involves using a laser beam to selectively melt metal powder with a desired shape on a substrate to create a part layer-by-layer. As an Additive Manufacturing (AM) process, laser powder bed fusion (commonly referred to as selective laser melting—SLM) offers superior design freedom over conventional manufacturing methods and enables the production of complex
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Development of a Versatile Mechanical Testing Device for In Situ Synchrotron Tomography and Diffraction Experiments Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-06-20 Maxime Pelerin; Andrew King; Lucien Laiarinandrasana; Henry Proudhon
A new mechanical stage to perform in situ 3D imaging using synchrotron X-ray tomography is presented. Pairing control and acquisition allows the running of high quality continuous mechanical tests to study damage and fracture in any kind of structural materials. The modular design make this device very versatile with the possibility to use many specimen geometries and load ranges up to 5 kN, and switch
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Probing Local Mechanical Properties in Polymer-Ceramic Hybrid Acetabular Sockets Using Spherical Indentation Stress-Strain Protocols Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-06-18 Hyung N. Kim; Sourav Mandal; Bikramjit Basu; Surya R. Kalidindi
Mechanical properties exhibited by the materials used in biomedical device components for articulating joints play an important role in determining the implant performance. In the fabrication of complex-shaped parts, the thermomechanical history experienced in different locations of the final part can be substantially dissimilar, which may lead to large differences in the local microstructures and
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3D Morphological Analysis and Synthesis of Industrial Materials Surfaces Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-06-18 Michael V. Glazoff
We present the original results pertaining to understanding topographical features on real industrial alloy surfaces. Quite often, such materials are subjected to different thermomechanical treatments with the goal of improving their yield strength, ductility, corrosion resistance, and other properties. Operations of casting, rolling, extruding, and stretching metal invariably leave their distinct
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AixViPMaP ® —an Operational Platform for Microstructure Modeling Workflows Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-06-07 L. Koschmieder; S. Hojda; M. Apel; R. Altenfeld; Y. Bami; C. Haase; M. Lin; A. Vuppala; G. Hirt; G.J. Schmitz
The present article describes design, architecture, and implementation of the Aachen (“Aix”) Virtual Platform for Materials Processing—AixViPMaP®. This simulation platform focuses on enabling automatic simulation workflows in the area of microstructure evolution and microstructure property relationships by continuum models. Following a description of a variety AixViPMaP® functionalities like user management
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Cloud-Based Materials and Product Realization—Fostering ICME Via Industry 4.0 Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-06-06 Anand Balu Nellippallil; Zhenjun Ming; Janet K. Allen; Farrokh Mistree
Facilitating integrated computational materials engineering (ICME) in the digitized world necessitates facilitating a network of participants (material scientists, systems designers, software developers, service customers) to share material/product/manufacturing process/market data, information, knowledge, and resources instantly and collaborate so as to facilitate a cost-effective co-creation of value
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A Tool to Generate Grain-Resolved Open-Cell Metal Foam Models Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-06-04 Joseph C. Tucker; Ashley D. Spear
The development and use cases of an open-source filter for DREAM.3D that instantiates synthetic, grain-resolved, open-cell metal foam volumes are presented. The new capability allows for both synthetic-grain overlay of X-ray computed tomography data as well as fully synthetic foam geometry and grains. For the latter, a novel technique using Euclidean distances instantiates the 3D open-cell foam morphology
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Bayesian Framework for Inverse Inference in Manufacturing Process Chains Integr. Mater. Manuf. Innov. (IF 3.447) Pub Date : 2019-05-28 Avadhut Sardeshmukh; Sreedhar Reddy; B. P. Gautham
Process-property relations are central to ICME. Engineers are often interested in using these relations to make decisions on process configurations to achieve desired properties. This is known as the inverse problem and is typically solved using forward models (physics-based or data-based) in an optimization loop, which can sometimes be expensive and error prone, especially when used on process chains