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ORGANIZER;CN=Michael McDonald:mailto:michael.mcdonald@fsu.edu
DESCRIPTION;LANGUAGE=en-US:"Predictive Design and Control of Fusion Pilot P
 lant Burning Plasmas"\n\nTomasz Plewa\nProfessor\, Department of Scientifi
 c Computing\nFlorida State University\n\nPlease feel free to forward/share
  this invitation with other groups/disciplines that might be interested in
  this talk/topic. All are welcome to attend.\n\nNOTE: In-person attendance
  is requested in our 499 Dirac Science Library (DSL) Seminar Room. Zoom ac
 cess is intended for external (non-departmental) participants only.\n\nhtt
 ps://fsu.zoom.us/j/94273595552\nMeeting # 942 7359 5552\n\n\n🎦 Colloqui
 um recordings will be made available here\, https://www.sc.fsu.edu/colloqu
 ium<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.
 sc.fsu.edu%2Fcolloquium&data=05%7C02%7Csc-seminar-announce%40lists.fsu.edu
 %7C1805eb52747d47bd945608de9fa58f7b%7Ca36450ebdb0642a78d1b026719f701e3%7C0
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 C%7C%7C&sdata=82eBRwR%2FXzkc0iM1sPLCFIVtHpcNpoFw%2BlTGiJ7Z%2FIs%3D&reserve
 d=0>\n\n\nWednesday\, Apr 22\, 2026\, Schedule:\n\n* 3:00 to 3:30 PM Easte
 rn Time (US and Canada)\n☕ Nespresso & Teatime - 417 DSL Commons\n\n* 3:
 30 to 4:30 PM Eastern Time (US and Canada)\n🕟 Colloquium - 499 DSL Semi
 nar Room\n\n\nAbstract:\nFusion energy is clean\, safe\, and effectively l
 imitless. This project builds the computational foundation needed to make 
 it practical — connecting rigorous physics\, NIF experimental data\, and
  modern AI into a single learning system that grows smarter as the plant o
 perates.\n\nA fusion pilot plant must fire a tiny hydrogen fuel capsule mi
 llions of times a year. Each shot must release more energy than it consume
 s. No human operator can adjust thousands of variables fast enough between
  shots. The plant needs to learn\, adapt\, and run itself.\n\nWe are build
 ing a digital twin of a fusion pilot plant burning core. A digital twin is
  a virtual replica that mirrors the real system in real time. It learns fr
 om data. It predicts what comes next. Eventually it controls the plant —
  shot by shot — without human intervention.\n\nThe first step is underst
 anding what happens inside the burning plasma. We have built a fast physic
 s model of the hot compressed core — the hot spot — that forms at the 
 moment of fusion. The model runs in seconds. We have tested it carefully a
 gainst known solutions\, then tuned it to match real NIF experiments — t
 he world's most powerful laser fusion facility. It correctly reproduces wh
 en ignition occurs\, how hot and dense the plasma gets\, and how much fuel
  is consumed.\n\nWe are using this model to generate large datasets of sim
 ulated shots. A machine learning surrogate will be trained on these datase
 ts. The surrogate will be thousands of times faster than the physics model
 . It will be embedded in the plant control system. After each real shot\, 
 the system reads the diagnostics\, updates its picture of the plasma\, and
  sets the conditions for the next shot — autonomously.\n\n\nAdditional c
 olloquium details can be found here.\nhttps://www.sc.fsu.edu/news-and-even
 ts/colloquium/1929-colloquium-with-tomasz-plewa-2026-04-22<https://nam04.s
 afelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fnews-a
 nd-events%2Fcolloquium%2F1929-colloquium-with-tomasz-plewa-2026-04-22&data
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SUMMARY;LANGUAGE=en-US:Scientific Computing Colloquium with Tomasz Plewa
DTSTART;TZID=Eastern Standard Time:20260422T153000
DTEND;TZID=Eastern Standard Time:20260422T162500
CLASS:PUBLIC
PRIORITY:5
DTSTAMP:20260421T125735Z
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