DMREF/Collaborative Research: Grain Interface Functional Design to Create Damage Resistance in Polycrystalline Metallic Materials
DMREF/Collaborative Research: Grain Interface Functional Design to Create Damage Resistance in Polycrystalline Metallic Materials
批准号:
2118399
负责人:
Curt Bronkhorst
金额:
$87.63万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-01-01 至 2025-12-31
中文摘要
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英文摘要
Even though polycrystalline metallic materials are ubiquitous in daily life, when and where metallic structural components damage and fail is difficult to predict, which generally leads to overdesign. One form of damage – ductile damage – takes place in materials which are easily plastically deformed by formation of voids and localized shear bands. The initiation of these voids is strongly influenced by the internal constitution of the aggregate composite made up of single crystals comprising the polycrystalline metal. High-purity metals often form voids at the boundaries between single crystals, but it is not known why. This Designing Materials to Revolutionize and Engineer our Future (DMREF) award supports the fundamental study of voids-based ductile damage in high-purity metals to enable the manufacture of materials for specific applications with significantly reduced propensity for void formation. In addition, this project will facilitate collaboration with the Air Force Research Laboratory to pursue design of new materials and manufacturing techniques for strategic purposes. This highly collaborative project will also allow students the opportunity to engage on three campuses, the Air Force Research Laboratory, and a couple of Department of Energy Laboratories to assist in educating the next generation of scientists and engineers in strategically important disciplines. Designing material interfaces to resist formation of voids during tensile deformation will be a significant contribution to the Materials Genome Initiative. This award addresses control of feature and defect character as well as the internal stress state for the design and manufacture of polycrystalline metals against failure. Ductile damage generally includes the processes of void nucleation, growth, and coalescence in addition to localized shear banding. This project is for a new three-dimensional sample design for both rod and plate forms of material, which will be a surrogate for a general structural component for large deformation. High-purity refractory body-centered cubic tantalum is selected as the model material due to its potential for extreme environment use. This material is known to form voids predominantly at grain boundaries and will be the focal point of material design through advanced manufacturing processes. The material design process will include the highly interactive elements of nano, micro and macro-scale experiments at varying strain rates and temperatures, molecular dynamics simulations, thermodynamically consistent plasticity and theory development, micro-scale polycrystal simulations, and macro-scale damage simulations for component design. The highlight of the approach is the uncertainty quantification via machine learning for self-consistent consolidation of large experimental and simulation datasets to guide material design and manufacturing process. The goal of this project is to design a manufacturing process to produce material which reduces damage by 30% over that in the as-received and annealed state.This project is jointly funded by the Division of Civil, Mechanical and Manufacturing Innovation (CMMI) in the Directorate for Engineering (ENG), the Divisions of Materials Research (DMR) and Mathematical Sciences (DMS) in the Directorate for Mathematical and Physical Sciences (MPS), and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
A causality-based learning approach for discovering the underlying dynamics of complex systems from partial observations with stochastic parameterization
一种基于因果关系的学习方法,用于通过随机参数化的部分观察发现复杂系统的潜在动态
DOI:
10.1016/j.physd.2023.133743
发表时间:
2023
期刊:
Physica D: Nonlinear Phenomena
影响因子:
--
作者:
[Chen, Nan, Zhang, Yinling]
通讯作者:
Zhang, Yinling
DOI:
10.1016/j.ijplas.2023.103529
发表时间:
2021-09
期刊:
International Journal of Plasticity
影响因子:
9.8
作者:
[Seunghyeon Lee;Hansohl Cho;C. Bronkhorst;R. Pokharel;D. Brown;B. Clausen;S. Vogel;V. Anghel;G. T. Gray;J. Mayeur]
通讯作者:
Seunghyeon Lee;Hansohl Cho;C. Bronkhorst;R. Pokharel;D. Brown;B. Clausen;S. Vogel;V. Anghel;G. T. Gray;J. Mayeur
Data-driven statistical reduced-order modeling and quantification of polycrystal mechanics leading to porosity-based ductile damage
数据驱动的统计降阶建模和多晶力学的量化导致基于孔隙度的延性损伤
DOI:
10.1016/j.jmps.2023.105386
发表时间:
2023
期刊:
Journal of the Mechanics and Physics of Solids
影响因子:
5.3
作者:
[Zhang, Yinling, Chen, Nan, Bronkhorst, Curt A., Cho, Hansohl, Argus, Robert]
通讯作者:
Argus, Robert
Collaborative Research: Coupled Explicit Thermodynamics of Plasticity - An Innovative Model for Twinning Crystals
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批准号:2051355
-
项目类别:Standard Grant
-
资助金额:$31.91万
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财政年份:2021
-
负责人:Curt Bronkhorst
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依托单位:
海外基金