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

点击翻译按钮获取中文摘要

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.