GOALI: Collaborative Research: Integrated Computational-Experimental Program for Ductility and Failure in Cast Aluminum Alloys

GOALI：协作研究：铸造铝合金延展性和失效的综合计算实验计划

• 批准号: 0309519
• 负责人: Bhaskar Majumdar
• 金额: --
• 依托单位: New Mexico Institute of Mining and Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-07-15 至 2007-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0309519&HistoricalAwards=false
• 关键词: GOALI; Collaborative; Research; Integrated; Computational

Integrated computational- experimental program for ductility and failure in cast aluminum alloys Somnath Ghosh, Bhaskar Majumdar and Steve Harris Today's The automotive industry is faced with major challenge of improvedmustis faced with major challenges to improve performance to and reduce weight ratio in order to meet lofty fuel efficiency and emissions standards at low cost. Improved mAs designs become more complex and the power output requirements increase, the practical limits of their ductility and ultimate strength are being reached.,. which Scrapped parts and downtime can cost a manufacturer millions of dollars in terms of scrapped parts and downtime. Compounding The proposed Industry-University Collaborative GOALI research is aimed at addressing thisese issues for meeting goals of materials with high ductility, ultimate strength and strength at low cost. It will build a collaborative relation between the Ohio State University (PI), New Mexico Institute of Technology and Ford Research Laboratory (industry partner) to launch an integrated experimental-computational research program. The program will augment a major thrust area at FRLord called Virtual Aluminum Casting or VAC that is targeted to (a) reduce product development time (b), improve quality and performance, and reduce scrap and (c) improve performance and lower weight, and (d) reduce costs. and cycle time. The proposed program will develop a system of experimentally validated adaptive multiple scale computational models for predicting localization and ductile fracture of cast Al-Si components from microstructural information and process conditions. The models will simulate the evolution of microstructural features such as voids and secondary phases into incipient cracks and determine how the loss of ductilityductile failure depends on alloy properties and on the , distributions and interactions of different phases in the microstructure. The mechanics of particle fracture, interface decohesion, matrix rupture and damage percolation through the dendritic network will be studied. The role of porosity size and distribution on failure will also be investigated. Various dDevelopmental modules will include: (i) Quantitative metallography using SEM, and orientation imaging microscopy (OIM), and microstructural characterization to identify and characterize critical microstructure features that control important material response; (ii) Mechanical tests accompanied bywith in-situ SEM and fracture surface observations, computer imaging and microstructural characterization observation to generate strain fields and to provide understanding of critical mechanisms in the failure process; (iii) Neutron diffraction measurements and Raman microprobe techniques for microstress evolution and probabilistic strength estimation of particles; (iv) Development of an adaptive multi-level model for multiple scale analysis to predict the failure process as a phenomenon of multi-scale incidence and propagation of cracks; (v) Development of image-based microstructural Voronoi Cell finite element model for efficient and accurate analysis of plastic deformation, strain localization and damage evolution in nonuniform heterogeneous microstructures; and (vi) Incorporation of a probabilistic analysis framework to account for the effect of input variabilities on ductility and failure. The major intellectual merit of the proposed research is in its innovative blend of state state-of of-the the-art computational tools andwith experimental methods to advance provide a comprehensive analysis tool and design methodology for advanced metallic materialscast metals to increase their effective utilization. The uniqueness of this approach is in the broad attack on the problem: (a) iIntroduction of adaptive hierarchical and multi-scale computational models, incorporating image-based microstructural models to depict the percolation of damage at different length scales;. T (b) he iIncorporation of detailed microstructures at the critical regions of evolving damage and localization is possible through the efficient and accurate Voronoi Cell finite elementFE model, being developed by the PI.; and (c) Robust validation of the models through rigorous feedback from multi-scale experiments and material characterization by using in-situ SEM, orientation imaging microscopy (OIM), in-situ neutron diffraction and Raman microprobe. To the best knowledge of the investigators, there is a lack of such a necessary comprehensive approach to the understanding of response and failure characteristics of complex cast microstructures. The program, upon completion, is expected towill provide a good understanding of stress and strain evolution ofin the the complex phases in cast Al, their strength levels, and damage initiation and percolation through the network of brittle, ductile and porous phases. The broader impact of the program will occur on two fronts. front, the It will reach beyond the automotive industry to aid the entire casting industry, where significant gains in alloying and solidification technology is are often stymied by unknowns regardingnot knowing how variability in material and process parameters affect damage tolerance and ductility. The methodology will allow industry be able to leapfrog thepresent technology and use these lightweight allows into in new safety -critical applications, armed with the knowledge that ductility and fracture can now be predicted with a reasonable degree of confidence. The second front will be oGraduate students will intern at FRL every summer and NMT students will have access to equipment at the national labs. As a consequence of the university-industry collaboration collaboration, students in this program will have a strong interaction with and mentorship from industrial researchers . There will also be student interaction with researchers at Sandia National Laboratory. researchers. In addition, the national laboratories will be involved in the experimental component of the work.