NRT-AI: Harnessing AI for Inverse Design Training in Advanced and Sustainable Composites (IDeAS Composites)

尽管复合材料的设计空间很大，但在性能、经济和环境目标与当前的设计和制造方法之间存在着巨大的差距。最令人震惊的是昂贵、长的开发周期和次优的设计，这些设计浪费资源并可能对环境和气候变化产生不利影响。这种差距的根本原因是缺乏对材料结构，工艺方法和参数对材料微观结构演变以及最终产品的物理，经济和环境性能的影响的详细了解。这个国家科学基金会研究培训（NRT），利用人工智能（AI）进行高级和可持续复合材料（IDEAS）的逆向设计培训，将通过物理信息，基于AI的建模和设计平台来培训学生，这将有助于发现新的复合材料形式和相关的新制造方法。克莱姆森大学的NRT奖项将通过由学术教师和行业研究人员共同指导的变革性AI时代课程，促进学员研究和发现途径的转变。IDEAS复合材料计划将培训总共50名学生;其中25名将是NRT资助的IDEAS研究员，其余25名将被确定为IDEAS学者。该计划将吸引来自计算机科学、数据科学、统计科学、机械工程、汽车工程和材料科学的学员，并将为学员提供一套与工业界共同培训的技能，以确保他们在人工智能时代取得成功。该NRT计划的研究主题是发现和调查基于物理学的基于机器学习的逆向设计平台的有效性，以开发新的复合材料架构和制造方法。该计划将培养一批研究生，他们具有广泛的交叉技能知识支持的深厚的专业知识，并为他们提供由学术和行业专家共同促进的独特的“DNA形”技能。具体而言，该计划将（1）通过构建“数字生命周期”来促进人工智能与复合材料逆向设计和制造创新交叉点的跨学科研究，这是一套用于模拟复合材料组件生命周期的高保真模型，研究机器学习方法在逆向复合材料结构和制造工艺设计中的应用，（2）探索研究生和本科生联合培养模式，包括复合材料反求设计和以工业应用为中心的研究设计、开发和示范（RD& D）项目;（3）创造一个多样化、公平和包容的环境，促进跨学科合作，使学员为需要独特的“DNA型”技能的职业做好准备;（4）建立跨学科教育计划，（a）培养下一代复合材料工程毕业生（第5年共50人），他们将拥有必要的人工智能逆向设计专业知识和技能，以应对即将到来的人工智能时代的独特挑战，并在复合材料行业蓬勃发展，和（B）培训现有的劳动力，以提高他们的知识，并促进人工智能方法和原则在复合材料工程界的传播。培训（NRT）计划旨在鼓励开发和实施大胆的，新的潜在变革模式，用于STEM研究生教育培训。该计划致力于通过创新的、基于证据的、与不断变化的劳动力和研究需求相一致的综合培训模式，在高优先级的跨学科或融合研究领域对STEM研究生进行有效培训。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Despite the vast design space of composites, there are significant gaps between the performance, economic, and environmental targets and current design and manufacturing approaches. Most egregious are the expensive, long development cycles and the sub-optimal design that waste resources and may adversely affect the environment and climate change. The fundamental cause of such gaps is the lack of detailed understanding of the influence of the material architecture, process methods, and parameters on material microstructure evolution and subsequently the end product’s physical, economic, and environmental performance. This National Science Foundation Research Traineeship (NRT), harnessing artificial intelligence (AI) for Inverse Design Training in Advanced and Sustainable Composites (IDeAS), will train students through a physics-informed, AI-based modeling and design platform which will enable the discovery of new composites materials forms and relevant new manufacturing methodologies. This NRT award to Clemson University will catalyze a shift in the research and discovery pathway of the trainees via a transformative AI-age curriculum co-instructed by academic faculty and industry researchers. The IDeAS Composites program will train a total of 50 students; of these, 25 will be NRT-funded IDeAS fellows and the remaining 25 would be identified as IDeAS scholars. The program will draw trainees from computer science, data science, statistical science, mechanical engineering, automotive engineering, and materials science and will empower trainees with an academia–industry co-trained skill set that will ensure their success in the AI age. The research theme of this NRT program is focused on discovering and investigating the effectiveness of a physics-informed, machine-learning-based inverse design platform for developing new composite material architectures and manufacturing methodologies. The program will train a cohort of graduate students with deep, specialized expertise supported by broad, cross-skill knowledge, and equip them with a unique “DNA-shaped” skill set collaboratively facilitated by both academic and industry experts. Specifically, the program will (1) catalyze interdisciplinary research at the intersection of AI and the inverse design of composites and manufacturing innovation via constructing a “digital life cycle” which is a suite of high-fidelity models for simulating a composite component’s life cycle, investigating the application of machine-learning methods for inverse composite material architecture and manufacturing process design, and developing an inverse design approach for integrated material and manufacturing design; (2) explore a combined graduate and undergraduate student training model comprising a composites inverse design capstone and a research design, development, and demonstration (RD&D) project centering on research outcomes applied to industry problems; (3) create a diverse, equitable, and inclusive environment fostering interdisciplinary collaboration in which trainees are prepared for careers requiring a unique “DNA-shaped” skill set; and (4) establish an interdisciplinary education program to (a) prepare next-generation composites engineering graduates (altogether 50 by year 5) who will have AI-enabled inverse design expertise and skills necessary to meet the unique challenges of the coming AI age and to thrive in the composites industry, and (b) train the current workforce to enhance their knowledge and foster dissemination of AI methods and principles in the composites engineering community.The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.  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.