Context Aware Machine Learning Approaches for Modeling Elastic Localization in Three-Dimensional Composite Microstructures [0.03%]
基于上下文的机器学习方法在三维复合材料微结构弹性局部化建模中的应用
Ruoqian Liu,Yuksel C Yabansu,Zijiang Yang et al.
Ruoqian Liu et al.
The response of a composite material is the result of a complex interplay between the prevailing mechanics and the heterogenous structure at disparate spatial and temporal scales. Understanding and capturing the multiscale phenomena is crit...
Extraction of Process-Structure Evolution Linkages from X-ray Scattering Measurements Using Dimensionality Reduction and Time Series Analysis [0.03%]
基于降维和时间序列分析的衍射数据中材料物相演变关系提取方法研究
David B Brough,Abhiram Kannan,Benjamin Haaland et al.
David B Brough et al.
The rapid development of robust, reliable, and reduced-order process-structure evolution linkages that take into account hierarchical structure are essential to expedite the development and manufacturing of new materials. Towards this end, ...
Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data [0.03%]
基于数据科学的方法研究工艺-组织构型关联：激光粉末床熔融镍基高温合金的模拟案例分析
Evdokia Popova,Theron M Rodgers,Xinyi Gong et al.
Evdokia Popova et al.
A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) proces...
Application-Specific Computational Materials Design via Multiscale Modeling and the Inductive Design Exploration Method (IDEM) [0.03%]
基于多尺度建模和归纳设计探索方法（IDEM）的专用计算材料设计
Brett D Ellis,David L McDowell
Brett D Ellis
The development of materials is a laborious, iterative, expensive, and intuitive process, often requiring decades to transition from early laboratory studies to commercial applications. This research seeks to address this issue by demonstra...
High throughput exploration of process-property linkages in Al-6061 using instrumented spherical microindentation and microstructurally graded samples [0.03%]
基于球形纳米压痕与组织梯度试样的6061铝合金高通量研究
Jordan S Weaver,Ali Khosravani,Andrew Castillo et al.
Jordan S Weaver et al.
Recent spherical nanoindentation protocols have proven robust at capturing the local elastic-plastic response of polycrystalline metal samples at length scales much smaller than the grain size. In this work, we extend these protocols to len...
Machine learning approaches for elastic localization linkages in high-contrast composite materials [0.03%]
机器学习在高对比复合材料中弹性局域链中的应用
Ruoqian Liu,Yuksel C Yabansu,Ankit Agrawal et al.
Ruoqian Liu et al.
There has been a growing recognition of the opportunities afforded by advanced data science and informatics approaches in addressing the computational demands of modeling and simulation of multiscale materials science phenomena. More specif...
Eric A Lass,Mark R Stoudt,Carelyn E Campbell
Eric A Lass
A systems approach within an Integrated Computational Materials Engineering framework was used to design three new low-cost seamless replacement coinage alloys to reduce the raw material of the current US coinage alloys. Maintaining compati...
Classification of Journal Articles in a Search for New Experimental Thermophysical Property Data: A Case Study [0.03%]
案例研究：在搜索新的实验热物性数据期刊文章分类
Adele P Peskin,Alden A Dima
Adele P Peskin
We present a case study in which we use natural language processing and machine learning techniques to automatically select candidate scientific articles that may contain new experimental thermophysical property data from thousands of artic...
Materials Knowledge Systems in Python - A Data Science Framework for Accelerated Development of Hierarchical Materials [0.03%]
Python中的材料知识系统——一种用于加速开发分层材料的数据科学框架
David B Brough,Daniel Wheeler,Surya R Kalidindi
David B Brough
There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Str...