Award Abstract # 2108320
Unified Framework for the Study of Alfven Wave Resonances, Magnetic Reconnection and Kelvin-Helmholtz Instabilities

NSF Org: PHY
Division Of Physics
Recipient: UNIVERSITY OF TEXAS AT AUSTIN
Initial Amendment Date: July 8, 2021
Latest Amendment Date: July 28, 2023
Award Number: 2108320
Award Instrument: Continuing Grant
Program Manager: Vyacheslav (Slava) Lukin
vlukin@nsf.gov
 (703)292-7382
PHY
 Division Of Physics
MPS
 Directorate for Mathematical and Physical Sciences
Start Date: August 1, 2021
End Date: December 31, 2025 (Estimated)
Total Intended Award Amount: $480,000.00
Total Awarded Amount to Date: $480,000.00
Funds Obligated to Date: FY 2021 = $320,810.00
FY 2023 = $159,190.00
History of Investigator:
  • Anna Tenerani (Principal Investigator)
    Anna.Tenerani@austin.utexas.edu
  • Tan Bui-Thanh (Co-Principal Investigator)
  • Francois Waelbroeck (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Texas at Austin
110 INNER CAMPUS DR
AUSTIN
TX  US  78712-1139
(512)471-6424
Sponsor Congressional District: 25
Primary Place of Performance: University of Texas at Austin
3925 W Braker Lane, Ste 3.340
Austin
TX  US  78759-5316
Primary Place of Performance
Congressional District:
37
Unique Entity Identifier (UEI): V6AFQPN18437
Parent UEI:
NSF Program(s): PLASMA PHYSICS,
MAGNETOSPHERIC PHYSICS,
PHYSICS-BROADEN PARTICIPATION,
CDS&E
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 8084, 8092, 5750, 1062, 026Z, 4444, 7621, 1242
Program Element Code(s): 124200, 575000, 762100, 808400
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.049

ABSTRACT

This award supports multidisciplinary work that builds on the synergy between theoretical plasma physics and computational applied mathematics to further our understanding of fundamental plasma processes. Plasma is a form of ionized matter that can be found everywhere in our universe. Neon lights, lightning, auroras and stars are all examples of matter in the plasma state. In a plasma, ions and electrons interact strongly with electric and magnetic fields causing unique and highly energetic phenomena, some of which have a direct impact on us - such as solar coronal mass ejections that may lead to space weather events on Earth. It is known that magnetic fields play a crucial role in this type of events by providing a means to store energy and to transport it through the propagation of waves. One of the fundamental open problems, however, is to understand how the energy stored in the magnetic fields is often impulsively released to the plasma in the forms of heat, accelerated particles, and radiation. This problem will be addressed under this award via cutting-edge theoretical and computational approaches. Numerical codes developed as part of this work will be open access to make computational resources accessible to a wider range of researchers and to students through the group's educational activities.

This project brings together decades of expertise in plasma physics, computational mathematics and high performance computing to investigate the processes of energy storage and release via the formation of boundary layers in high Lundquist number plasmas. Dissipation of magnetic waves, known as Alfven waves, and the reconnection of magnetic field lines are often invoked as possible mechanisms to explain plasma energization. However, our understanding of how such mechanisms can give rise to impulsive energization is still incomplete, and it remains challenging due to the disparate spatial and temporal scales of the phenomena involved. To address this fundamental issue, this project focuses on the role of mass flows in the interaction of Alfven wave resonances, Kelvin-Helmholtz instability, and magnetic reconnection in two- and three-dimensional systems. To this end, the project will rely on state-of-the-art codes and develop high-order hybridized discontinuous finite element codes to achieve the required resolution to simulate energetic events. Graduate students will be supported to work on the project, who will greatly benefit from the broad impacts of this research on both plasma physics and software cyberinfrastructure.

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

Note:  When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

(Showing: 1 - 10 of 12)
Lee, Jeonghun J. and Bui-Thanh, Tan and Villa, Umberto and Ghattas, Omar "Forward and inverse modeling of fault transmissibility in subsurface flows" Computers & Mathematics with Applications , v.128 , 2022 https://doi.org/10.1016/j.camwa.2022.09.013 Citation Details
Nguyen, Hai V. and Bui-Thanh, Tan "A Model-Constrained Tangent Slope Learning Approach for Dynamical Systems" International Journal of Computational Fluid Dynamics , v.36 , 2022 https://doi.org/10.1080/10618562.2022.2146677 Citation Details
Nguyen, Hai Van and Chen, Jau-Uei and Bui-Thanh, Tan "A model-constrained discontinuous Galerkin Network (DGNet) for compressible Euler equations with out-of-distribution generalization" Computer Methods in Applied Mechanics and Engineering , v.440 , 2025 https://doi.org/10.1016/j.cma.2025.117912 Citation Details
Wittmer, Jonathan and Badger, Jacob and Sundar, Hari and Bui-Thanh, Tan "An autoencoder compression approach for accelerating large-scale inverse problems" Inverse Problems , v.39 , 2023 https://doi.org/10.1088/1361-6420/acfbe1 Citation Details
Wittmer, Jonathan and Krishnanunni, C G and Nguyen, Hai V and Bui-Thanh, Tan "On unifying randomized methods for inverse problems" Inverse Problems , v.39 , 2023 https://doi.org/10.1088/1361-6420/acd36e Citation Details
Muralikrishnan, Sriramkrishnan and Shannon, Stephen and Bui-Thanh, Tan and Shadid, John N. "A multilevel block preconditioner for the HDG trace system applied to incompressible resistive MHD" Computer Methods in Applied Mechanics and Engineering , v.404 , 2023 https://doi.org/10.1016/j.cma.2022.115775 Citation Details
Steins, Ella and BuiThanh, Tan and Herty, Michael and Müller, Siegfried "Probabilistic constrained Bayesian inversion for transpiration cooling" International Journal for Numerical Methods in Fluids , v.94 , 2022 https://doi.org/10.1002/fld.5135 Citation Details
Urbanski, D and Tenerani, A and Waelbroeck, FL "Unified framework of forced magnetic reconnection and Alfvén resonance" Fundamental Plasma Physics , 2024 https://doi.org/10.1016/j.fpp.2024.100064 Citation Details
Chen, Jau-Uei and Kang, Shinhoo and Bui-Thanh, Tan and Shadid, John N "A unified hp-HDG framework for Friedrichs' PDE systems" Computers & Mathematics with Applications , v.154 , 2024 https://doi.org/10.1016/j.camwa.2023.12.009 Citation Details
Bui-Thanh, Tan "A unified and constructive framework for the universality of neural networks" IMA Journal of Applied Mathematics , 2023 https://doi.org/10.1093/imamat/hxad032 Citation Details
Chen, Jau-Uei and Horváth, Tamás L and Bui-Thanh, Tan "A divergence-free and H(div) -conforming embedded-hybridized DG method for the incompressible resistive MHD equations" Computer Methods in Applied Mechanics and Engineering , v.432 , 2024 https://doi.org/10.1016/j.cma.2024.117415 Citation Details
(Showing: 1 - 10 of 12)

Please report errors in award information by writing to: awardsearch@nsf.gov.

Print this page

Back to Top of page