| NSF Org: |
PHY Division Of Physics |
| Recipient: |
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| Initial Amendment Date: | July 18, 2018 |
| Latest Amendment Date: | July 18, 2018 |
| Award Number: | 1820852 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Bogdan Mihaila
bmihaila@nsf.gov (703)292-8235 PHY Division Of Physics MPS Directorate for Mathematical and Physical Sciences |
| Start Date: | September 1, 2018 |
| End Date: | August 31, 2022 (Estimated) |
| Total Intended Award Amount: | $283,348.00 |
| Total Awarded Amount to Date: | $283,348.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
70 WASHINGTON SQ S NEW YORK NY US 10012-1019 (212)998-2121 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
251 Mercer Street New York NY US 10012-1019 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
PLASMA PHYSICS, COMPUTATIONAL PHYSICS, CDS&E-MSS |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.049 |
ABSTRACT
A growing number of technologies rely on the production of energetic beams of charged particles in accelerators for their operation. Proton therapy for cancer treatment and food irradiation to eliminate pathogens are among the most remarkable applications. These successes are paving the way for new applications for particle accelerators, such as materials science experiments and nuclear waste transmutation, which would require much more intense beams than are currently available. A difficulty is that at such high beam intensities, beam induced damages on the accelerator structures cannot be tolerated. Achieving a high beam quality throughout the acceleration process thus becomes a critical issue. The dynamics of beams in accelerators is described by equations which can only be accurately solved with long and expensive simulations run on supercomputers. Accelerator design studies therefore involve time consuming, computer intensive simulations, limiting the range of design options which can be investigated. This project addresses this limitation by developing a numerical method that will significantly reduce the run times of existing numerical codes while maintaining a high level of accuracy. By accelerating beam dynamics simulations in accelerators, the new solver will help improve design optimization for the next generation of high intensity accelerators.
The purpose of this project is to develop new methods to predict the dynamics of high intensity beams in cyclotrons. The beam dynamics is described by the Vlasov equation, a six-dimensional nonlinear partial differential equation, and quantitative results can only be obtained through numerical simulation. Particle codes based on the Particle-In-Cell (PIC) algorithm have been successfully used for this purpose. Still, a limitation of these codes is that a large number of particles need to be followed to limit statistical error, which leads to long run times. To reduce run times, the PI and graduate students will develop a novel noise reduction technique for the standard PIC algorithm, based on the use of sparse grids. In order to maximize the leverage from this new technique, they will implement high performance algorithms in their sparse-PIC solver, and optimize the sparse grids using model reduction techniques tailored for cyclotron simulations. At every stage of the development of the solver, they will compare the performance of the new code with the state-of-the-art code OPAL. The code will be available to collaborators at major cyclotron facilities to answer unresolved questions regarding the stability of high intensity beams in cyclotrons and to design new machines.
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
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The purpose of this project was to develop mathematical methods and numerical codes that would accelerate simulations of the dynamics of beams in particle accelerators as well as the dynamics of a hot and diffuse form of matter called plasma. Simulating the evolution of these physical systems has a high computational cost, to be measured in days and weeks even when simulations are run on the most powerful supercomputers. Furthermore, in order to make these simulations computationally tractable, scientists rely on numerical approximations of the actual physical systems. These approximations have the adverse effect of adding artificial noise to the simulations, which limits their accuracy.
We constructed a mathematical framework and designed and implemented computer codes which reduce this artificial noise. With our approach, simulations yield a more accurate description of the true physical evolution for a given computational cost. Equivalently, for a given target accuracy of the computational model, our method reduces the computational run time and the demands on computational resources.
During the course of this first project, we realized that our noise reduction strategy could be reinterpreted in terms of a method commonly used in the field of uncertainty quantification. This new understanding motivated us to explore a research direction we had not anticipated in our original proposal. Specifically, we considered a quintessential uncertainty quantification problem for scientists who need to design experiments able to confine, with external magnetic coils, energetic charged particles over long time scales. Since in most applications the energetic particles are born from nuclear fusion reactions or are injected inside the experiment with a device with limited accuracy, there is uncertainty in the initial velocity direction and initial speed of the energetic particles. The codes scientists use to estimate the fraction of energetic particles which will be lost during the experiment suffer from high numerical noise as they attempt to account for the uncertainty in the initial conditions of the energetic particles.
We adapted several recent noise reduction methods to the particular needs of these magnetic confinement applications, and showed for the first time how to combine these numerical schemes to enhance the accuracy of the estimation of the fraction of particles that will be lost before the end of the experiment. In our applications, our new codes accelerated this estimation by a factor of more than 100 for a given target accuracy.
The last part of the research work supported by this grant was not anticipated at the beginning of the project either. Having gained experience, via our two other projects, with the magnetic confinement of particles and with uncertainty quantification, we were able to develop new numerical codes for the optimization and design of magnetic coils accounting for coil manufacturing and placement uncertainties. With our efficient codes, we were able to design coils generating magnetic fields with excellent confinement properties, and which ensure good confinement even if one adds random perturbations to the shapes of the coils and their location, provided the magnitude of the perturbations is comparable to manufacturing tolerances.
These projects were originally formulated and proposed by mid-career PIs, but all the detailed mathematical and computational work was done by post-doctoral scientists as well as graduate and undergraduate students. Our research work thus contributed to training a new generation of computational scientists, who is ready to fill key positions in universities, national laboratories, and high technology companies. The members of our team were encouraged to present their work at conferences and discuss their results in group meetings. Doing so, they had many opportunities to improve and practice their communication skills, which will enable them to be inspiring and effective leaders, as well as transmit their knowledge to a new generation of scientists.
Last Modified: 02/01/2023
Modified by: Antoine Cerfon
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