Collaborative Research: Software Engineering Workforce Development in High Performance Computing for Digital Twins

该项目将有助于满足国家对生产工程中受过良好教育的工程师和技术人员的需求。它将通过支持田纳西大学查塔努加分校和田纳西理工大学举办的两个为期两天的生产工程教育研讨会来实现这一目标。讲习班的总体目标是为数字孪生研究和开发的快速扩展的生产技术推荐教育方法。数字孪生是流程、产品或服务的虚拟模型。这种虚拟世界和物理世界的结合使系统分析和改进成为可能，包括生产工程系统。例如，通过首先在数字孪生体中开发新的效率，然后在物理孪生体中进行测试，可以改进流程和产品。预计这些研讨会将有助于实现可扩展、可靠和具有成本效益的战略，以创建准确代表复杂系统的数字孪生，如制造业和化工厂、飞机和风力涡轮机。这些研讨会还将有助于制定指导方针，培训在生产工程和其他应用中开发和实施数字孪生所需的STEM劳动力。第一次研讨会将在田纳西大学查塔努加分校举行，并将产生一份报告，描述多学科对在生产工程中使用数字孪生的智力贡献。第二次研讨会将于四个月后在田纳西理工大学举行，将产生一份报告，描述数字孪生生产工程教育的课程建议。这些研讨会将召集高性能计算、软件工程、不确定性量化、控制系统、数字孪生模型和仿真以及工程教育方面的思想领袖，以制定与数字孪生相关的有效、创新、分布式教育的建议，特别是在生产工程方面。此外，它们有望在教育研究和设计、实施和操作数字孪生所需的多学科领域的交叉领域产生融合研究项目。在研讨会上，这些学科将聚集在一起，建立教育的概念模型，使工人能够设计更好地与生产工程环境相结合的数字双胞胎。教育工作者和领域专家之间的合作有望出现，产生诸如高性能仿真和机器学习软件系统的增强设计等成果，这些系统既能响应不断变化的生产环境需求，又适合在课堂和虚拟环境中使用。该项目由美国国家科学基金会EHR核心研究：生产工程教育与研究（ECR: PEER）项目资助，该项目旨在改善未来和当前生产工程专业人员的教育。它还旨在研究这些项目所采用的创新教育策略的有效性。该奖项反映了美国国家科学基金会的法定使命，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。

This project will contribute to the national need for well-educated engineers and technicians in production engineering. It will do so by supporting two, two-day workshops on production engineering education by the University of Tennessee Chattanooga and Tennessee Technological University. The overall goal of the workshops is to recommend educational approaches for the rapidly expanding production technology of digital twin research and development. A digital twin is a virtual model of a process, product, or service. This pairing of virtual and physical worlds enables analysis and improvement of systems, including production engineering systems. For example, by developing new efficiencies first in the digital twin, and then testing them in the physical twin, processes and products can be improved. It is expected that these workshops will contribute to achieving scalable, reliable, and cost-effective strategies for creation of digital twins that accurately represent complex systems, such as manufacturing and chemical plants, airplanes, and wind turbines. The workshops will also contribute to developing guidelines for training the STEM workforce needed to develop and implement digital twins in production engineering and other applications. The first workshop will be held at the University of Tennessee Chattanooga and will result in a report describing the intellectual contributions of multiple disciplines to the use of digital twins in production engineering. The second workshop, to be held at Tennessee Technological University four months later, will result in a report describing curriculum recommendations for digital twin production engineering education.These workshops will convene thought leaders in high-performance computing, software engineering, uncertainty quantification, control system, digital twin modeling and simulation, and engineering education to develop recommendations for effective, innovative, distributed education related to digital twins, particularly in production engineering. In addition, they are expected to lead to convergent research projects at the intersection of educational research and the multidisciplinary areas needed to design, implement, and operate digital twins. At the workshops, these disciplines will come together to establish conceptual models for education that will prepare workers to design digital twins that better integrate with production engineering environments. Collaborations are expected to emerge between educators and domain experts, yielding outcomes such as the enhanced design of high-performance simulation and machine learning software systems that are both responsive to evolving needs of production environments and suitable for use in classroom and virtual environments.This project is funded by NSF's EHR Core Research: Production Engineering Education and Research (ECR: PEER) program, which seeks to improve the education of future and current professionals in production engineering. It also aims to study the effectiveness of the innovative educational strategies adopted by these projects.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.