Collaboration fuses codes for efficient simulation

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Without adaptive meshes, the program would have had to simulate a larger pellet, a smaller reactor, and a weaker magnetic field around the plasma, Samtaney says.  Such a simplified simulation would have limited use.

Fusion reactor refueling simulation using AMR to capture the detail of what happens when a tiny frozen pellet is injected into a huge hot plasma cloud. (Click image for larger view and more info)

The goal is to solve the engineering problem of refueling the fusion reactor, Samtaney says.  But a more important goal is understanding how the pellet’s mass is distributed in the plasma.

“That kind of quantitative information would be very useful for ITER,” Samtaney says, but obtainable only with detailed simulation.

Real problems improve codes

The collaboration was just as valuable for the Berkeley group, Colella says.

“There’s nothing like having a real problem, and a new real problem, something we haven’t done before,” to improve software, he adds.  Besides making their codes more applicable, the fusion simulation helped expose areas where the codes slow.

“It is very valuable for us to get that kind of feedback, because then you can go and fix those problems,” Colella says.

Colella says Samtaney also succeeded in bringing a new approach to simulating physics.  Although trained in the similar field of computational fluid dynamics, Samtaney had to teach himself plasma physics when he started at Princeton five years ago.

Now “I think he’s viewed as a member of the club” by the physicists he works with, Colella says.

Samtaney says those challenges are some of the best things about his job.  Another is “I get to work with absolutely the best people in this business,” Samtaney adds.  “Phil Colella and his staff members are the best.”

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