PSFC Seminars

Seminars are currently being held virtually. 
For further information & zoom link:
PSFC address: NW17-218, 175 Albany Street, Cambridge

Oct 7, 2022

Progress and challenges for fusion materials

Steven Zinkle

Oak Ridge National Laboratory

 As noted during the recent US fusion community R&D prioritization planning evaluation and accompanying DOE-Fusion Energy Sciences Advisory Committee and National Academies assessments, and spurred by increased private sector investments, there is growing interest in boldly proceeding with construction of a fusion demonstration reactor. Advanced materials will be foundational for the successful operation of any next-step fusion energy device. This presentation will provide an overview of some of the key advances achieved with respect to fusion materials during the past 10 years, along with an assessment of several key remaining challenges. A brief summary of potential candidate materials (focusing on structural materials) and key degradation mechanisms (primarily associated with exposure to D-T fusion neutrons) will be given.

3:00pm  |  NW17-218 Hybrid  |  Add to CalendarApple CalendarGoogleOutlookYahoo

Oct 18, 2022


Speakers: Fusion leaders, including Dennis Whyte, MIT

At this hybrid event, taking place virtually and at the Museum of Science, London, PSFC Director Dennis Whyte will speak on "What does fusion need: Solutions to technical challenges." Register here

5:30am  |  Science Museum, London and virtual  |  Add to CalendarApple CalendarGoogleOutlookYahoo

Past Events

Aug 26, 2022

CPS-FR: Magnetic control of TCV tokamak plasmas through Deep Reinforcement Learning

Federico Felici

Swiss Plasma Center, EPFL

A key challenge in tokamak operations is to shape and maintain a high-temperature plasma within the vessel. This requires regulating the plasma position and shape via magnetic fields generated by a set of control coils. This work presents a new architecture for designing a tokamak magnetic controller based on deep reinforcement learning. The controller is entirely trained on a physics-based simulator and then deployed on the TCV tokamak hardware, where it was successful in controlling a diverse set of plasma configurations, including a new configuration featuring two plasmas in the vessel simultaneously. The control architecture replaces separate controllers used in traditional architectures with a single control policy. This lecture will provide details about the training and deployment of the reinforcement learning algorithm, as well as providing a comparison with more traditional control engineering solutions to the magnetic control problem.
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Password: 843110

4:00pm  |  Virtual

Aug 24, 2022

CPS-FR: Software Productivity and Sustainability in Computational Science

Anshu Dubey

Argonne National Laboratory

In this lecture I will describe challenges of improving software productivity in computational science projects, especially those that involve high performance computing. I will also describe various efforts in mitigating these challenges through distillation of practices that have been found to be effective. The topics covered will include software design for performance portability and sustainability, and methodologies for increasing both the scientific output and the developer productivity.  Join Zoom Meeting

Password: 783470

4:00pm  |  Virtual

Aug 23, 2022

CPS-FR: Machine learning and Bayesian modeling at Wendelstein 7-X

Andrea Pavone

Institute of Plasma Physics

Through applications related to the Wendelstein 7-X fusion experiment, the speaker will demonstrate how Bayesian inference can enhance the exploitation of interdependent heterogeneous sources of information, such as plasma diagnostic measurements, in a complex system through physics-based modeling and conventional inference methods (MCMC, MAP), and how it can benefits from recent advances based on deep learning to scale up to the large amount of data and systems found in nowadays fusion experiments.  Join Zoom Meeting

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4:00pm  |  Virtual

Aug 22, 2022

CPS-FR: Part 2. Optimizing the performance of fusion reactors with transport in the loop

Noah Mandell


As we approach the breakeven era of fusion, optimizing reactors to make them more efficient and less expensive will be critical to the wide-scale adoption of fusion as a commercial energy source. The main challenge is to achieve and maintain high steady-state pressures in the core of the reactor to reach self-sustaining fusion conditions. Since turbulence is the main source of heat transport and losses, there is an opportunity for improving reactor performance by optimizing the design for turbulent transport.  Join Zoom Meeting:
Password: 649687

4:45pm  |  Virtual

Aug 22, 2022

CPS-FR: Part 1. Optimization projects for the advancement of fusion energy

Pablo Rodriguez-Fernandez


This talk will present examples of the application of surrogate-based optimization techniques to solve fusion-relevant modeling problems, such as a gyrokinetic profile predictor and an equilibrium solver suitable for exploratory applications. The use of gaussian process regression within a Bayesian optimization framework is demonstrated to accelerate the design process of fusion reactors through the development of computationally efficient modeling workflow.   Join Zoom Meeting:
Password: 649687

4:00pm  |  Virtual

Aug 22–27, 2022

Computational Physics School for Fusion Research (CPS-FR) 2022

The CPS-FR aims at providing young researchers with critical skill sets to tackle modern fusion energy research challenges through hands-on tutorials and classes. Topics:  High Performance Computing (HPC);  Parallel Programming and GPU Computing; Computational Statistics; Machine Learning;  Registration closes May 29.

9am - 5:30am daily  |  MIT campus building 4-231

May 24, 2022

Neutron irradiation effects on the superconducting performance of REBCO coated conductors

Michael Eisterer

TU Wien, Atominstitut, Vienna, Austria

I will review our findings of neutron irradiation experiments in our in-house research reactor over the last 15 years. After having established the peak in critical current as a function of neutron fluence, we investigated the universality of this behavior followed by attempts to explain it by the competing effects of added pinning centers and reduced superfluid density. Recently, we started annealing experiments to devise mitigation strategies against the adverse effects of neutron radiation.

2:00pm  |  NW17-218 Hypbrid

May 18, 2022

The physics basis for WHAM and breakeven in a Compact High Field Mirror

Cary Forest

University of Wisconsin-Madison

An overview of the design for the Wisconsin HTS Axisymmetric Mirror. The experiment has been funded by ARPA-E and is a partnership between the UW Madison, MIT and Commonwealth Fusion Systems has been formed to build and operate a compact, high-field simple mirror WHAM. Success will demonstrate a pathway to a cost-effective VNS for blanket testing and other applications requiring a large flux of 14 MeV neutrons, and also show how compact end plugs can now be built for axisymmetric tandem mirrors.

1:30pm  |  NW17-218 Hybrid

May 13, 2022

Tritium experiments and isotope studies in JET with ITER-like wall

Costanza Maggi


Starting from the motivation of Tritium experiments in JET with ITER-like wall, the talk will then cover some of the aspects of tokamak operations with Tritium. The talk will then continue with a review of main scientific results obtained in JET-ILW encompassing all three hydrogen isotopes to understand the dependence of particle, heat and momentum transport on isotope mass, required for predicting ITER's burning plasmas.

10:00am  |  Virtual

May 11, 2022

The Electromagnetic Particle Injector (EPI) as a fast time response disruption mitigation system for tokamak-based reactors

Roger Ramen

University of Washington, Seattle

Predicting and controlling disruptions is an important and urgent issue for ITER. Some disruptions with a short warning time may be unavoidable. For these cases, a fast time response disruption mitigation method is essential. Experimental tests on a prototype system of a novel, rapid time-response disruption mitigation system being developed for tokamak-based reactors, referred to as the Electromagnetic Particle Injector (EPI), has been able to verify the primary advantages of the concept.

1:30pm  |  NW17-218 Hybrid

May 6, 2022

LIBRA: Liquid Immersion Blanket, Robust (Tritium) Accountancy

Sara Ferry


This seminar will introduce LIBRA, a major new experimental platform to study FLiBe tritium breeding in a large (~1000 kg) volume of FLiBe in a 14 MeV neutron spectrum. We are presently preparing for the construction of LIBRA and its associated lab space at the MIT PSFC. LIBRA will be the most comprehensive FLiBe tritium breeding experiment ever constructed, and targets an aggressive timeline for the rapid advancement of the TRL of FLiBe breeding blankets.

3:00pm  |  NW17-218 Hypbrid

Apr 21, 2022

JET DTE2 campaign: preparation, execution and selected highlights

Joelle Mailloux


In 2021, high fusion power deuterium-tritium experiments (DTE2) were performed in JET for the first time since the 1997 D-T campaigns in TFTR and JET (DTE1). This talk will explore the latest results.

10:00am  |  Virtual

Apr 1, 2022

Physics considerations for the ITER first wall lifetime

Richard Pitts


This presentation will describe some of the recent physics efforts which have been made at the ITER Organization and with R&D collaborators to provide the FW lifetime estimates which are being used now to guide decisions on the procurement of FWP spares.

10:00am  |  Virtual

Mar 21, 2022

Theory of nonlinear ELMs as reconnection bursts

Fatima Ebrahimi

Princeton Plasma Physics Laboratory

A presentation of new results on the rise and nonlinear relaxation of Peeling-Ballooning ELMs (Edge-Localized Modes).The formation of current sheets and the transition to 3-D current-sheet instability is demonstrated through fully nonlinear resistive MHD simulations of P-B ELMs in DIII-D discharges. Large-scale axisymmetric current sheets, as well as small-scale poloidally extending current sheets, are formed as the coherent P-B ELM filaments nonlinearly evolve. A  model for the magnetic self-organization during nonlinear ELMs is presented.


Mar 15, 2022

Combining simulation and machine learning with experiment to drive the future of fusion energy

Michael Churchill

Princeton Plasma Physics Laboratory

In this seminar, the speaker will show how fast, deep convolutional neural networks can be applied to multi-scale plasma diagnostics to automate prediction and event identification. Next, he will show how normalizing flows can be used as neural density estimators to both speed up Bayesian inference of physical quantities from experimental diagnostic data, and in uncertainty quantification of ad-hoc inputs to scrape-off layer fluid codes, consistent with experimental data (simulation-based inference). Finally, he will discuss the role of large-scale, high-fidelity first-principles simulation, such as the edge gyrokinetic code XGC, and how these can be accelerated with machine learning for more routine use in plasma modeling.