GOALI: Data-driven design of recycling tolerant aluminum alloys incorporating future material flows

目标：数据驱动的可回收铝合金设计，结合未来的材料流

• 批准号: 2243914
• 负责人: Elsa Olivetti
• 金额: $ 34.29万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2243914&HistoricalAwards=false
• 关键词: GOALI; Data; driven; design; recycling

Metals production contributes to 8% of greenhouse gas emissions worldwide. Improving materials efficiency must play a role in decarbonizing metals production because such strategies are available now and achievable along a shorter time horizon than novel production methods. One strategy to improve material consumption is through improved materials recovery using recycling. Recycling is particularly beneficial for aluminum, where energy benefits from use of recycled materials are much improved relative to primary consumption. Significantly improved recycling, both in terms of quantity and quality, can play a role in achieving decarbonization targets over the necessary greenhouse gas reduction timeline. To this end, metals production industries have set goals to increase the use of recycled content. In the face of an evolving scrap stream and shifts in product demand, these targets will not be achievable without coupling alloy design with considerations of future end-of-life scrap streams. However, alloy design has traditionally focused on improving performance without much regard for environmental impact or the ability to recycle the materials. This project will design new alloys by including recyclability in addition to performance metrics into the design process accounting for how scrap streams are expected to evolve in the future.The goal of this project is to create a design pipeline that can be used alongside traditional alloy design to create recycling-friendly alloys. Recycling-friendly alloys are defined as alloys that can incorporate a lot of scrap in their production (sink) but that can also be used in the production of a lot of other alloys (source). This research will address this trade-off between sink and source by (i) creating a materials distribution model to inform recycling and future scrap streams, (ii) developing a Bayesian optimization algorithm to effectively explore the alloy space, and (iii) identifying the design space using constraints on alloys compositions and properties. The material distribution model will be a combination of material flow analysis and blending model that will inform the future material streams (compositions, quantities, prices of scrap streams and future demand) and how those can be used to produce new alloys. This model will then be maximized over the alloy space using the efficient optimization method. Finally, the optimization to find the best alloy will be subject to constraints on compositions, thermodynamic quantities, and properties. Overall, this work focuses on alloy design that optimizes scrap use in projected material flows by integrating a materials distribution model, efficient optimization, and constrained design space. Since these elements have never been integrated together, not only is the approach unique, but the integration involves advances in each of these areas. Thus, the proposed work represents a step forward in sustainable alloy design and integrates and innovates on previously developed approaches in this area.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.

金属生产占全球温室气体排放量的8%。提高材料效率必须在脱碳金属生产中发挥作用，因为这样的策略现在是可用的，并且比新的生产方法在沿着更短的时间内可以实现。改善材料消耗的一项战略是通过利用回收来改善材料回收。回收利用对铝特别有利，其中使用回收材料的能源效益相对于初级消费有很大改善。在数量和质量方面显著改善回收利用，可以在必要的温室气体减排时间轴内实现脱碳目标。为此，金属生产行业已经制定了增加回收成分使用的目标。面对不断变化的废料流和产品需求的变化，如果不将合金设计与未来报废废料流的考虑结合起来，这些目标将无法实现。然而，合金设计传统上专注于提高性能，而不太考虑环境影响或材料回收的能力。该项目将通过在设计过程中考虑废料流在未来的发展方式，将可回收性和性能指标纳入新合金的设计中。该项目的目标是创建一个设计管道，可以与传统合金设计一起使用，以创建回收友好型合金。回收友好型合金被定义为在生产过程中可以包含大量废料的合金（汇），但也可以用于生产许多其他合金（源）。本研究将通过以下方式解决汇和源之间的这种权衡：（i）创建材料分布模型，以通知回收和未来的废料流，（ii）开发贝叶斯优化算法，以有效地探索合金空间，以及（iii）使用对合金成分和性能的约束来确定设计空间。材料分配模型将是材料流分析和混合模型的组合，将告知未来的材料流（成分，数量，废料流的价格和未来需求）以及如何使用这些来生产新合金。然后使用有效的优化方法在合金空间上最大化该模型。最后，找到最佳合金的优化将受到成分、热力学量和性能的约束。总的来说，这项工作的重点是合金设计，优化废料的使用，在预计的材料流整合材料分布模型，有效的优化，并限制设计空间。由于这些要素从未被整合在一起，因此不仅方法独特，而且整合涉及这些领域中的每一个。因此，该项目代表了可持续合金设计的一个进步，并整合和创新了该领域先前开发的方法。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。