Conference: 20th Biennial CTR Summer Program

This award will partially cover travel expenses of invited speakers and student participants and organizing expenses related to the workshop entitled "The Center for Turbulence Research (CTR) Summer Program," to be held at Stanford University. The program is scheduled to be held at Stanford from June 26 to July 24, 2026. Participants will include faculty, graduate students, and a cadre of 10-20 postdocs that will assist visitors to promote successful outcomes in every research project. The 2024 program was the largest to date with 103 external participants from 15 countries, including participants from 60 institutions. The participants included experimentalists, theoreticians, and computational scientists. A competitive process will be used to select participants based on their research credentials, the merits of their research proposals and the relevance to areas of interest to CTR. Graduate students will be accepted to accompany their research advisors.

One goal of the workshop will be to frame the challenges in turbulence modeling for the next few years. The findings of the program will be collected and published as a comprehensive technical report. The report is expected to consist of forty to fifty technical papers (about 500 pages) which will be delivered to NSF and to other sponsors of the program and disseminated worldwide at the end of the calendar year. The report, like the reports from the prior workshops, will be available at https://ctr.stanford.edu/summer-program. Many papers in the report will be eventually published in high quality technical journals. The bulk of the CTR Summer Programs will involve hands-on interrogation of numerical simulation databases for testing models and hypotheses proposed by the participants. Additional calculations to generate new databases may be performed during the summer. The participants will be divided into focus groups based on their proposed areas of research. Emphasis will be placed on proposals in advanced computing (e.g., mixed precision arithmetic and quantum computing), machine learning for uncertainty quantification and turbulence modeling. Other topics of interest will include, control, sensing, non-equilibrium flows, data compression, and model reduction.

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.

Award Number: 2621560
Principal Investigator: Parviz Moin
Funds Obligated: $40,000
State: CA