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Whole Device Modelingof Compact Tori: Stability and Transport Modeling of C-2W

Whole Device Modelingof Compact Tori: Stability and Transport Modeling of C-2W

Oct 2017 | Research Library,  Posters, Fusion Energy, Fusion Research, Fusion Science, Fusion Technology, Modeling, Overview, Plasma Research, Simulation, Stability, Transport

October 2017 | Sean Dettrick | APS-DPP | Poster

TAE is working towards catalysing a community-wide collaboration to develop a Whole Device Model (WDM) of Compact Tori.

Overview of the C-2W Field-Reversed Configuration Experiment Diagnostic Suite

Overview of the C-2W Field-Reversed Configuration Experiment Diagnostic Suite

Oct 2017 | Research Library,  Posters, Diagnostics, Experiment, Fusion Energy, Fusion Research, Fusion Science, Fusion Technology, Overview, Plasma Research

October 2017 | M. C. Thompson | APS-DPP | Poster

Tri Alpha Energy (TAE) studies the evolution of advanced beam-driven field-reversed configuration (FRC) plasmas sustained by neutral-beam injection.

Overview of C-2W Field-Reversed Configuration Experimental Program

Overview of C-2W Field-Reversed Configuration Experimental Program

Oct 2017 | Research Library,  Posters, Confinement, Experiment, Formation, Fusion Energy, Fusion Research, Fusion Science, Fusion Technology, Overview, Performance, Plasma Research

October 2017 | H. Gota | APS-DPP | Poster

Tri Alpha Energy’s research has been devoted to producing a high temperature, stable, long-lived field-reversed configuration (FRC) plasma state by neutral-beam injection (NBI) and edge biasing/control.

C-2U Physics Overview

C-2U Physics Overview

May 2017 | Research Library,  Posters, Diagnostics, Experiment, Fusion Energy, Fusion Research, Fusion Science, Fusion Technology, Plasma Research

May 2017 | A. Necas | The Sherwood Fusion Theory Conference | Poster

C-2U is a unique hybrid field-reversed configuration (FRC) where we successfully combine a high-beta (~1) FRC plasma with neutral beam injection (NBI), field line biasing, and mirror physics.

FRC separatrix inference using machine learning techniques

FRC separatrix inference using machine learning techniques

Nov 2016 | Performance,  Presentations, Fusion Energy, Fusion Research, Fusion Science, Fusion Technology, Plasma Research, Research Library

November 2016 | J. Romero | APS-DPP | Presentation

Method to infer the FRC separatrix geometry and axial stability properties of the equilibrium developed. Tested with equilibrium code simulations

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