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Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:UNIVERSITY OF WASHINGTON
Doing Business As Name:University of Washington
PD/PI:
  • Uri Shumlak
  • (206) 616-1986
  • shumlak@aa.washington.edu
Award Date:06/08/2021
Estimated Total Award Amount: $ 360,000
Funds Obligated to Date: $ 360,000
  • FY 2021=$360,000
Start Date:06/15/2021
End Date:05/31/2024
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.049
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:Multiscale Phenomena in Plasmas from Collisional to Collisionless Regimes
Federal Award ID Number:2108419
DUNS ID:605799469
Parent DUNS ID:042803536
Program:PLASMA PHYSICS
Program Officer:
  • Vyacheslav (Slava) Lukin
  • (703) 292-7382
  • vlukin@nsf.gov

Awardee Location

Street:4333 Brooklyn Ave NE
City:Seattle
State:WA
ZIP:98195-0001
County:Seattle
Country:US
Awardee Cong. District:07

Primary Place of Performance

Organization Name:University of Washington
Street:4333 Brooklyn Ave NE
City:Seattle
State:WA
ZIP:98195-0001
County:Seattle
Country:US
Cong. District:07

Abstract at Time of Award

This project seeks to develop a numerical model of a plasma - a gas of electrically charged particles - that will combine a very detailed description of plasma processes on small scales with a coarser description of large scales. Scientific understanding is advanced through the development and application of mathematical models that accurately describe natural phenomena. The highest fidelity models provide the most accurate description but are often too difficult to solve. Simplified models are easier to solve but can fail to capture the relevant interactions that dictate a system’s evolution. This project seeks to develop a hybrid model that stitches together high-fidelity and low-fidelity descriptions. The low-fidelity component is applied to all domains where the model is formally valid, and the high-fidelity component is applied only where it is absolutely required. The hybrid model will be applied to study the evolution of magnetized flowing plasmas, similar to the situation that occurs as plasma flowing from the Sun interacts with Earth's magnetosphere. Understanding these interactions can provide predictions about energy transfer between spatial scales that can ultimately impact GPS and communication satellites. This project aims to develop a new approach to explore multiscale phenomena in plasmas and to investigate the magnetized Kelvin-Helmholtz instability (KHI). Plasmas inherently exhibit multiscale physics that originate from the large differences in electron and ion masses of the constituent species and from the long-range and short-range interactions that are produced by electromagnetic fields and collisions. However, capturing the large separation of scales in simulations remains an outstanding challenge. Collisionality expresses the relative importance of long-range and short-range interactions and can play an important role in determining the spread and coupling of scales. Models that are accurate in the highly collisional regime fail in the collisionless regime, while models that are accurate in the collisionless regime are computationally prohibitive in the collisional regime. Exploiting the computational efficiency of multi-fluid models and the high-fidelity of kinetic models, a hybrid approach will be developed to couple the models through domain decomposition to explore multiscale phenomena. Continuum representations for the fluid and kinetic models will facilitate coupling through moments of the probability distribution functions of the constituent plasma species. The magnetized KHI is known to develop macroscale plasma structures whose details depend on microscale physics. The hybrid model will be applied to study the magnetized KHI to gain insight into the interplay between the multiple scales that ultimately drive transport and dictate the partition of energy. 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.

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