GOALI: Development of Lightweight Structural Castings Using an Integrated Computational Materials Engineering Approach

金属铸造是制造航空航天、汽车、化工、能源、医疗保健和消费品行业中使用的部件的一种非常有效的工艺。目前工业中金属铸件的设计经常导致材料性能不均匀，其中零件或组件的强度可能在整个件中变化。这通常通过过度设计材料来补偿，以确保最小的强度，并可能导致不必要的材料浪费和制造时间。该学术与工业联络资助机会（GOALI）项目旨在开发计算和实验工具，以构建具有定制属性的部件，旨在在部件承受最大载荷的区域具有最高强度。这个项目将结合计算材料工程和实验工作来创建和测试这个量身定制的设计系统。这种方法将导致快速和高效的铸造设计和制造工艺的发展，从而发现新的高性能合金和轻质铸件，这将减少能源消耗和浪费。该项目结合了材料设计和制造工艺开发，采用相图计算（CALPHAD）和工艺模拟的混合方法，更快地设计出用于下一代汽车和航空航天结构的轻质铝铸件。这种新颖的方法将合金成分和热处理的热力学预测与工艺建模联系起来，利用美国铝业公司正在开发的新型高性能铝合金的特定位置特性，设计出更高效的铸件。这项跨学科的研究将用于开发铸造设计、合金设计和工艺优化的集成模型，这是将计算热力学与部件设计联系起来的第一次尝试。设计和仿真结果将通过试样和汽车铸件的选择性实验来验证。具体而言，为实现项目目标，俄亥俄州立大学（OSU）和美国铝业公司将开展四项研究任务：1)凝固和热处理的CALPHAD建模和合金设计；2)基于calphhad相平衡数据的工艺模拟与优化；3)利用CALPHAD和过程建模的混合方法预测的特定位置属性进行组件设计，以满足特定位置的服务负载条件；4)用试样和汽车铸件进行试验验证。

Metal casting is a very efficient process of manufacturing components used in the aerospace, automotive, chemical, energy, healthcare, and consumer products industries. Current design of metal castings in industries often results in non-uniform material properties, where the strength of the part or component may vary throughout the piece. This is often compensated for by the over-design of materials to ensure a minimum strength, and can result in unnecessary waste of materials and manufacturing time. This Grant Opportunity for Academic Liaison with Industry (GOALI) project seeks to develop computational and experimental tools to build parts with tailored properties, designed to have the highest strength in the areas where the part will bear the most load. This project will integrate computational materials engineering with experimental work to create and test this tailored design system. This approach will lead to fast and efficient casting design and manufacturing process development, resulting in discoveries of new high-performance alloys and lightweight castings which will reduce energy consumption and waste. This project combines material design and manufacturing process development using a hybrid approach of CALPHAD (CALculation of PHAse Diagrams) and process simulation to more rapidly design lightweight aluminum castings for next generation automotive and aerospace structures. This novel approach will connect the thermodynamic prediction of alloy composition and heat treatment to process modeling to design more efficient castings using location-specific properties of new high-performance aluminum alloys being developed by Alcoa. This interdisciplinary research will be carried out to develop an integrated model for casting design, alloy design and process optimization - a first attempt to connect computational thermodynamics to component design. The design and simulation results will be validated by selective experimentation in test specimens and an automotive casting. Specifically, four research tasks will be carried out between The Ohio State University (OSU) and Alcoa to achieve the project goal: 1) CALPHAD modeling of solidification and heat treatment and alloy design; 2) process simulation and optimization using CALPHAD phase equilibria data; 3) component design using location-specific properties predicted by the hybrid approach of CALPHAD and process modeling to meet the location-specific service loading conditions; and 4) experimental validation using test specimens and an automotive casting.