Integrating Materials and Manufacturing Innovation最新文献_第6页

Coupled Thermal Solidification Process Simulation of Sapphire Growth 蓝宝石生长的耦合热凝固过程模拟

IF 3.3 3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-12-14 DOI: 10.1007/s40192-023-00321-7

{"title":"Coupled Thermal Solidification Process Simulation of Sapphire Growth","authors":"","doi":"10.1007/s40192-023-00321-7","DOIUrl":"https://doi.org/10.1007/s40192-023-00321-7","url":null,"abstract":"<h3>Abstract</h3> Thermal distribution during the sapphire growth process determines to a great extent the thermal stresses and dislocation density in sapphire. In this work, thermal and defect simulations of sapphire growth in a simplified single-boule furnace are presented. The heat transfer in the furnace is modeled via ANSYS Fluent® by considering conduction, convection and radiation effects. A dislocation density-based crystal plasticity model is applied for the numerical simulation of dislocation evolution during the crystal growth of sapphire. The physical models are validated by using a temporal series of measurements in the real furnace geometry, which capture the crystal–melt interface position during the technological growth process. The growth rate and the shape of the crystal growth front are analyzed for different side and top heater powers which result in different thermal distributions in the furnace. It is found that the cooling flux at the crucible bottom wall determines to a great extent the growth profile in the first half of the growth stage. Only toward the end of the growth stage, different top and side power distributions induce different growth front shapes. The effect of the convexity of the growth surface on the generation of dislocation defects is investigated by the crystal plasticity model. The results of simulations show that the convexity of the growth surface has a significant effect on the generation of dislocations.","PeriodicalId":13604,"journal":{"name":"Integrating Materials and Manufacturing Innovation","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138680938","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

Laser Powder Bed Fusion Process and Structure Data Set for Process Model Validations 用于工艺模型验证的激光粉末床融合工艺和结构数据集

IF 3.3 3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-12-13 DOI: 10.1007/s40192-023-00323-5

Nathaniel Wood, Edwin Schwalbach, Andrew Gillman, David J. Hoelzle

引用次数: 0

Image Processing Pipeline for Fluoroelastomer Crystallite Detection in Atomic Force Microscopy Images 用于在原子力显微镜图像中检测氟橡胶结晶的图像处理管道

IF 3.3 3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-12-08 DOI: 10.1007/s40192-023-00320-8

Mingjian Lu, Sameera Nalin Venkat, Jube Augustino, David Meshnick, Jayvic Cristian Jimenez, Pawan K. Tripathi, Arafath Nihar, Christine A. Orme, Roger H. French, Laura S. Bruckman, Yinghui Wu

{"title":"Image Processing Pipeline for Fluoroelastomer Crystallite Detection in Atomic Force Microscopy Images","authors":"Mingjian Lu, Sameera Nalin Venkat, Jube Augustino, David Meshnick, Jayvic Cristian Jimenez, Pawan K. Tripathi, Arafath Nihar, Christine A. Orme, Roger H. French, Laura S. Bruckman, Yinghui Wu","doi":"10.1007/s40192-023-00320-8","DOIUrl":"https://doi.org/10.1007/s40192-023-00320-8","url":null,"abstract":"Phase transformations in materials systems can be tracked using atomic force microscopy (AFM), enabling the examination of surface properties and macroscale morphologies. In situ measurements investigating phase transformations generate large datasets of time-lapse image sequences. The interpretation of the resulting image sequences, guided by domain-knowledge, requires manual image processing using handcrafted masks. This approach is time-consuming and restricts the number of images that can be processed. In this study, we developed an automated image processing pipeline which integrates image detection and segmentation methods. We examine five time-series AFM videos of various fluoroelastomer phase transformations. The number of image sequences per video ranges from a hundred to a thousand image sequences. The resulting image processing pipeline aims to automatically classify and analyze images to enable batch processing. Using this pipeline, the growth of each individual fluoroelastomer crystallite can be tracked through time. We incorporated statistical analysis into the pipeline to investigate trends in phase transformations between different fluoroelastomer batches. Understanding these phase transformations is crucial, as it can provide valuable insights into manufacturing processes, improve product quality, and possibly lead to the development of more advanced fluoroelastomer formulations.","PeriodicalId":13604,"journal":{"name":"Integrating Materials and Manufacturing Innovation","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138555995","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

Temperature-Dependent Material Property Database for C63200 Nickel-Aluminum Bronze (NAB) Plate C63200镍铝青铜(NAB)板的温度相关材料性能数据库

IF 3.3 3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-12-06 DOI: 10.1007/s40192-023-00325-3

Sean M. Orzolek, Justin E. Norkett, Charles R. Fisher

引用次数: 0

A Transformer and Random Forest Hybrid Model for the Prediction of Non-metallic Inclusions in Continuous Casting Slabs 用变压器和随机森林混合模型预测连铸板坯中非金属夹杂物

IF 3.3 3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-11-27 DOI: 10.1007/s40192-023-00312-8

Zexian Deng, Yungui Zhang, Lin Zhang, Junqiang Cong

{"title":"A Transformer and Random Forest Hybrid Model for the Prediction of Non-metallic Inclusions in Continuous Casting Slabs","authors":"Zexian Deng, Yungui Zhang, Lin Zhang, Junqiang Cong","doi":"10.1007/s40192-023-00312-8","DOIUrl":"https://doi.org/10.1007/s40192-023-00312-8","url":null,"abstract":"Non-metallic inclusions (NMIs) in continuous casting slabs will significantly reduce the performance of final steel products and lead to other defects in steel products. The traditional detection methods of NMIs in continuous casting slabs have the problem of low efficiency, and it is complicated to establish a prediction model of NMIs based on physics and chemistry. Therefore, we tried to use the machine learning method by integrating Transformer and Random Forest and established an RF-1DViT model to predict NMIs in continuous casting slabs. To predict the occurrence and the location of NMIs as accurately as possible, the whole process data of steelmaking, refining and continuous casting were used, and the continuous casting slab was processed in slices. The experimental results show that the proposed RF-1DViT model has an F1 score of 0.8991, surpassing Logical Regression, K-Nearest Neighbor, Support Vector Machine, Random Forest, AdaBoost, GradientBoost, Multi-Layer Perceptron and 1DViT model, and has good interpretability and strong feature extraction ability. By means of the Random Forest and histogram, the process importance can be analyzed and rules of inclusions generation can be given. The t-SNE manifold learning method can further assist researchers to accurately locate the defect.","PeriodicalId":13604,"journal":{"name":"Integrating Materials and Manufacturing Innovation","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138512547","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

Lifetime and Degradation Study of Poly(Methyl Methacrylate) via a Data-Driven Study Protocol Approach 基于数据驱动研究方案的聚甲基丙烯酸甲酯寿命和降解研究

IF 3.3 3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-11-22 DOI: 10.1007/s40192-023-00322-6

Hein Htet Aung, Donghui Li, Jiqi Liu, Chiara Barretta, Yiyang Sheng, Yea Jin Jo, Jayvic C. Jimenez, Erika I. Barcelos, Gernot Oreski, Roger H. French, Laura S. Bruckman

{"title":"Lifetime and Degradation Study of Poly(Methyl Methacrylate) via a Data-Driven Study Protocol Approach","authors":"Hein Htet Aung, Donghui Li, Jiqi Liu, Chiara Barretta, Yiyang Sheng, Yea Jin Jo, Jayvic C. Jimenez, Erika I. Barcelos, Gernot Oreski, Roger H. French, Laura S. Bruckman","doi":"10.1007/s40192-023-00322-6","DOIUrl":"https://doi.org/10.1007/s40192-023-00322-6","url":null,"abstract":"To optimize and extend the service life of polymeric materials in outdoor environments, a domain knowledge-based and data-driven approach was utilized to quantitatively investigate the temporal evolution of degradation modes, mechanisms, and rates under various stepwise accelerated exposure conditions. Six formulations of poly(methyl methacrylate) (PMMA) with different combinations of stabilizing additives, including one unstabilized formulation, were exposed in three accelerated weathering conditions. Degradation was dependent on wavelength as samples in UV light at 340 nm (UVA) exposure showed the most yellowing. The unstabilized PMMA formulation showed much higher yellowness index values (59.5) than stabilized PMMA formulations (2–12). Urbach edge analysis shows a shift toward longer wavelength from 285 to 500 nm with increasing exposure time and an increased absorbance around 400 nm of visible region as the unstabilized samples increase in yellowing. The degradation mechanisms of PMMA were tracked using induced absorbance to dose at specific wavelengths that correspond to known degradation mechanisms. The degradation pathway of PMMA was modeled in a <Stressor | Mechanism | Response> framework using network structural equation modeling (netSEM). netSEM showed changes in degradation pathway as PMMA transition stages of degradation.","PeriodicalId":13604,"journal":{"name":"Integrating Materials and Manufacturing Innovation","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138512546","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

Process–Structure–Property Simulation Approach to the Estimation of Tensile Anisotropy in 3D Printed Meta-stable $$beta $$ Titanium Alloy 3D打印亚稳定钛合金拉伸各向异性估算的工艺-结构-性能模拟方法$$beta $$

IF 3.3 3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-11-15 DOI: 10.1007/s40192-023-00319-1

Luis M. Reig Buades, Martin P. Persson

{"title":"Process–Structure–Property Simulation Approach to the Estimation of Tensile Anisotropy in 3D Printed Meta-stable $$beta $$ Titanium Alloy","authors":"Luis M. Reig Buades, Martin P. Persson","doi":"10.1007/s40192-023-00319-1","DOIUrl":"https://doi.org/10.1007/s40192-023-00319-1","url":null,"abstract":"Developing accurate process–structure–property models for metal additive manufacturing is crucial due to the numerous process parameters, extended build times, and high material costs which make it impractical to rely solely on an experimental trial and error approach when optimizing the process. In this work, a multiscale digital approach to estimate tensile anisotropy along selective laser melted titanium meta-stable (beta ) alloys is presented. The approach uses a component scale thermal FEA model of the process to calculate temperature, a meso-scale phase field model to calculate microstructure evolution, and a microscale crystal plasticity model to calculate the effect of texture on the tensile properties in different directions. The model has predicted isotropic yield strength for this material, which could guide designers to choose orientations freely. However, anisotropy in hardening behavior could be expected but is caused by porosity and cracking, which are not considered in the presented models. We believe the presented approach, which relies solely on easy to use commercial simulation tools, lays a good foundation for the development of process–structure–property models to optimize process parameters. The modeling approach should be applicable to other mechanical properties and materials with appropriate considerations.","PeriodicalId":13604,"journal":{"name":"Integrating Materials and Manufacturing Innovation","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138512556","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

Review of Material Modeling and Digitalization in Industry: Barriers and Perspectives 工业材料建模与数字化:障碍与展望

3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-11-10 DOI: 10.1007/s40192-023-00318-2

Lucia Scotti, Hector Basoalto, James Moffat, Daniel Cogswell

{"title":"Review of Material Modeling and Digitalization in Industry: Barriers and Perspectives","authors":"Lucia Scotti, Hector Basoalto, James Moffat, Daniel Cogswell","doi":"10.1007/s40192-023-00318-2","DOIUrl":"https://doi.org/10.1007/s40192-023-00318-2","url":null,"abstract":"Abstract Materials modeling technologies are fundamental to explore, understand, and ultimately predict materials behavior. They are essential to solve challenges posed by the need to reduce human impact on the environment. Modeling and simulation of materials behavior have been recognized over the years as fundamental as an asset in industrial R & D, guiding the decision-making process regarding the design or optimization of new products and manufacturing processes. At the same time, it reduces product cost and development time. However, highlighting the revenue brought by using such tools is not trivial, especially because they mainly affect the complex activities such as the innovation process, whose return only becomes available in the long run and it is difficult to measure. This means that the materials modeling field is often overlooked in an industry setting, where it is not integrated in the company workflow. In some cases, modeling provides the potential to capture tacit knowledge preventing the loss of capability in an aging specialist community, that why its industrial integration is important. This paper explores the reason behind this dichotomy, presenting first what it is intended for the modeling process, and the main types used in materials application. The current industrial adoption is reviewed by outlining success stories, economic impact, business uptake, and barriers. Past and current approaches and strategies are also presented and discussed. In prospective, materials modeling plays a key role in developing material-centric industry for sustainable economy, providing physical understating (physics-based models) and fast approaches (data-driven solutions). Digitalization is the mean for the green economy and it needs to push for a more integration at the core of the business of materials modeling.","PeriodicalId":13604,"journal":{"name":"Integrating Materials and Manufacturing Innovation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135136525","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

Study of TIG Weld Microstructure Formation in Inconel 718 Alloy Using ICME Approach 用ICME法研究Inconel 718合金TIG焊缝组织形成

3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-11-07 DOI: 10.1007/s40192-023-00317-3

Shambhu Kushwaha, M. Agilan, M. R. Rahul, Gandham Phanikumar

引用次数: 0

Design and Optimization of Manufacturing Process of Polymer Composites Through Multiscale Cure Analysis and NSGA-II 基于多尺度固化分析和NSGA-II的聚合物复合材料制造工艺设计与优化

3区材料科学

Integrating Materials and Manufacturing Innovation Pub Date : 2023-11-03 DOI: 10.1007/s40192-023-00316-4

Yagnik Kalariya, Soban Babu Beemaraj, Amit Salvi

引用次数: 0