Integrating Materials and Manufacturing Innovation最新文献_第7页

Multi-physics Approach to Predict Fatigue Behavior of High Strength Aluminum Alloy Repaired via Additive Friction Stir Deposition 添加剂搅拌摩擦沉积修复高强铝合金疲劳行为的多物理场预测

3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-11-01 DOI: 10.1007/s40192-023-00309-3

N. I. Palya, K. A. Fraser, Y. Hong, N. Zhu, M. B. Williams, K. Doherty, P. G. Allison, J. B. Jordon

{"title":"Multi-physics Approach to Predict Fatigue Behavior of High Strength Aluminum Alloy Repaired via Additive Friction Stir Deposition","authors":"N. I. Palya, K. A. Fraser, Y. Hong, N. Zhu, M. B. Williams, K. Doherty, P. G. Allison, J. B. Jordon","doi":"10.1007/s40192-023-00309-3","DOIUrl":"https://doi.org/10.1007/s40192-023-00309-3","url":null,"abstract":"Abstract A smooth particle hydrodynamic (SPH) simulation of an additive friction stir deposition (AFSD) repair was used to inform a multi-physics approach to predict the fatigue life of a high strength aluminum alloy. The AFSD process is a solid-state layer-by-layer additive manufacturing approach in which a hollow tool containing feedstock is used to deposit material. While an understanding of the evolving microstructures is necessary to predict material performance, the elevated temperatures and strain rates associated with severe plastic deformation processes (SPDP) make accurate collection of experimental data within AFSD difficult. Without the ability to experimentally determine material history within the AFSD process, an SPH model was employed to predict the thermomechanical history. The SPH simulation of an AFSD repair was used to inform several microstructural models to predict material history during and after processing with AFSD and a post-processing heat treatment. These microstructure models are then used to inform a mechanistic microstructure and performance model to predict the fatigue life of an AFSD repair in AA7075.","PeriodicalId":13604,"journal":{"name":"Integrating Materials and Manufacturing Innovation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135326243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Workflow for Accelerating Multimodal Data Collection for Electrodeposited Films 加速电沉积薄膜多模态数据采集的工作流程

3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-10-26 DOI: 10.1007/s40192-023-00315-5

Kimberly L. Bassett, Tylan Watkins, Jonathan Coleman, Nathan Bianco, Lauren S. Bailey, Jamin Pillars, Samuel Garrett Williams, Tomas F. Babuska, John Curry, Frank W. DelRio, Amelia A. Henriksen, Anthony Garland, Justin Hall, Brandon A. Krick, Brad L. Boyce

{"title":"A Workflow for Accelerating Multimodal Data Collection for Electrodeposited Films","authors":"Kimberly L. Bassett, Tylan Watkins, Jonathan Coleman, Nathan Bianco, Lauren S. Bailey, Jamin Pillars, Samuel Garrett Williams, Tomas F. Babuska, John Curry, Frank W. DelRio, Amelia A. Henriksen, Anthony Garland, Justin Hall, Brandon A. Krick, Brad L. Boyce","doi":"10.1007/s40192-023-00315-5","DOIUrl":"https://doi.org/10.1007/s40192-023-00315-5","url":null,"abstract":"Abstract Future machine learning strategies for materials process optimization will likely replace human capital-intensive artisan research with autonomous and/or accelerated approaches. Such automation enables accelerated multimodal characterization that simultaneously minimizes human errors, lowers costs, enhances statistical sampling, and allows scientists to allocate their time to critical thinking instead of repetitive manual tasks. Previous acceleration efforts to synthesize and evaluate materials have often employed elaborate robotic self-driving laboratories or used specialized strategies that are difficult to generalize. Herein we describe an implemented workflow for accelerating the multimodal characterization of a combinatorial set of 915 electroplated Ni and Ni–Fe thin films resulting in a data cube with over 160,000 individual data files. Our acceleration strategies do not require manufacturing-scale resources and are thus amenable to typical materials research facilities in academic, government, or commercial laboratories. The workflow demonstrated the acceleration of six characterization modalities: optical microscopy, laser profilometry, X-ray diffraction, X-ray fluorescence, nanoindentation, and tribological (friction and wear) testing, each with speedup factors ranging from 13–46x. In addition, automated data upload to a repository using FAIR data principles was accelerated by 64x.","PeriodicalId":13604,"journal":{"name":"Integrating Materials and Manufacturing Innovation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134908528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Tempered Hardness Optimization of Martensitic Alloy Steels 马氏体合金钢回火硬度优化

3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-10-26 DOI: 10.1007/s40192-023-00311-9

Heather A. Murdoch, Daniel M. Field, Benjamin A. Szajewski, Levi D. McClenny, Andrew Garza, Berend C. Rinderspacher, Mulugeta A. Haile, Krista R. Limmer

引用次数: 0

Predicting Sintering Window of Binder Jet Additively Manufactured Parts Using a Coupled Data Analytics and CALPHAD Approach 应用耦合数据分析和CALPHAD方法预测粘结剂喷射增材制造零件的烧结窗口

3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-10-25 DOI: 10.1007/s40192-023-00313-7

Rangasayee Kannan, Peeyush Nandwana

引用次数: 0

CAROUSEL: An Open-Source Framework for High-Throughput Microstructure Simulations CAROUSEL:一个高通量微观结构模拟的开源框架

3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-10-23 DOI: 10.1007/s40192-023-00314-6

Sebastian Carrion Ständer, Nora Barschkett, Evgeniya Kabliman

{"title":"CAROUSEL: An Open-Source Framework for High-Throughput Microstructure Simulations","authors":"Sebastian Carrion Ständer, Nora Barschkett, Evgeniya Kabliman","doi":"10.1007/s40192-023-00314-6","DOIUrl":"https://doi.org/10.1007/s40192-023-00314-6","url":null,"abstract":"Abstract High-throughput screening (HTS) can significantly accelerate the design of new materials, allowing for automatic testing of a large number of material compositions and process parameters. Using HTS in Integrated Computational Materials Engineering (ICME), the computational evaluation of multiple combinations can be performed before empirical testing, thus reducing the use of material and resources. Conducting computational HTS involves the application of high-throughput computing (HTC) and developing suitable tools to handle such calculations. Among multiple ICME methods compatible with HTS and HTC, the calculation of phase diagrams known as the CALPHAD method has gained prominence. When combining thermodynamic modeling with kinetic simulations, predicting the entire history of precipitation behavior is possible. However, most reported CALPHAD-based HTS frameworks are restricted to thermodynamic modeling or not accessible. The present work introduces CAROUSEL—an open-sourCe frAmewoRk fOr high-throUghput microStructurE simuLations. It is designed to explore various alloy compositions, processing parameters, and CALPHAD implementations. CAROUSEL offers a graphical interface for easy interaction, scripting workflow for advanced simulations, the calculation distribution system, and simulation data management. Additionally, CAROUSEL incorporates visual tools for exploring the generated data and integrates through-process modeling, accounting for the interplay between solidification and solid-state precipitation. The application area is various metal manufacturing processes where the precipitation behavior is crucial. The results of simulations can be used in upscale material models, thus covering different microstructural phenomena. The present work demonstrates how CAROUSEL can be used for additive manufacturing (AM), particularly for investigating different chemical compositions and heat treatment parameters (e.g., temperature, duration).","PeriodicalId":13604,"journal":{"name":"Integrating Materials and Manufacturing Innovation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135412672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Part Deflection Measurements of AM‑Bench IN718 3D Build Artifacts AM - Bench IN718 3D构建工件的零件挠度测量

3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-10-06 DOI: 10.1007/s40192-023-00310-w

Maxwell Praniewicz, Jason C. Fox, Jared Tarr

引用次数: 0

VAMPYR: A MATLAB-Based Toolset Leveraging MTEX for Automating VPSC VAMPYR:利用MTEX实现VPSC自动化的基于matlab的工具集

3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-10-03 DOI: 10.1007/s40192-023-00308-4

B. A. Begley, V. M. Miller

引用次数: 0

A Case Study of Beta-Variational Auto-encoders, Disentanglement Impacts of Input Distribution and Beta-Variation Based Upon a Computational Multi-modal Particle Packing Simulation 基于计算多模态粒子堆积模拟的贝塔变分自动编码器、输入分布和贝塔变分的解纠缠影响的案例研究

IF 3.3 3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-09-01 DOI: 10.1007/s40192-023-00306-6

Jason R. Hall, Taylor D. Sparks

引用次数: 0

Additive Manufacturing Benchmark 2022 Subcontinuum Mesoscale Tensile Challenge (CHAL-AMB2022-04-MeTT) and Summary of Predictions 增材制造基准2022亚连续介质中尺度拉伸挑战(CHAL-AMB2022-04-MeTT)和预测摘要

3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-09-01 DOI: 10.1007/s40192-023-00307-5

Orion L. Kafka, Jake Benzing, Newell Moser, Li-Anne Liew, Jordan Weaver, Nikolas Hrabe

引用次数: 0

Restoration of Noisy Orientation Maps from Electron Backscatter Diffraction Imaging 电子后向散射衍射成像中噪声取向图的恢复

IF 3.3 3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-08-28 DOI: 10.1007/s40192-023-00304-8

Emmanuel Atindama, P. Lef, G. Dogan, Prashant Athavale

引用次数: 0