33 citations · 93 across the 22 of their papers we have counts for
25 papers
Applications of Poincaré Boundary Condition for 3D Ideal MHD Equilibrium and Optimization
Yigit Gunsur Elmacioglu, Dario Panici, Rory Conlin +2
Stellarator ideal magnetohydrodynamic (MHD) codes that assume nested flux surfaces such as \texttt{VMEC} and \texttt{DESC} solve the equilibrium problem by prescribing the total to…
AI-Accelerated Gyrokinetic Predictions of Turbulent Transport for Stellarator Design Optimization and Experimental Planning
R. Michael Churchill, Matt Landreman, Jong Youl Choi +10
Previous work built AI-based surrogates for a nonlinear gyrokinetic simulation code with the goal of using them for fast, direct calculations of turbulent ion heat flux in stellara…
yancc: A GPU-accelerated, differentiable solver for neoclassical transport in tokamaks and stellarators
Rory Conlin, Matt Landreman
We present yancc, a new GPU-accelerated solver for the drift kinetic equation that computes neoclassical transport fluxes, flows, and currents in tokamaks and stellarators. The dri…
Bayesian optimization of stellarator alpha-particle confinement using data-informed parameter spaces and dimensionality reduction
Matt Landreman, Michael Czekanski, Andrew Giuliani +2
Modern stellarators are typically designed by optimizing the shape of the plasma boundary surface, with the parameters taken to be Fourier amplitudes. Many promising optimization a…
Deflation Techniques for Stellarator Equilibrium and Optimization
Dario Panici, Byoungchan Jang, Rory Conlin +3
Stellarator optimization is a multi-objective, non-convex problem characterized by a complex objective landscape containing many local minima. The solution resulting from a single…
Narrow Operator Models of Stellarator Equilibria in Fourier Zernike Basis
Timo Thun, Rory Conlin, Dario Panici +1
Numerical computation of the ideal Magnetohydrodynamic (MHD) equilibrium magnetic field is at the base of stellarator optimisation and provides the starting point for solving more…
Exponential Spectral Scaling: Robust and Efficient Stellarator Boundary Optimization via Mode-Dependent Scaling
Byoungchan Jang, Rory Conlin, Matt Landreman
Stellarator boundary optimization faces a fundamental numerical challenge: the extreme disparity between low- and high-mode amplitudes creates an optimization landscape in which di…
Surface Current Optimization and Coil-Cutting Algorithms for Stage-Two Stellarator Optimization
Dario Panici, Rory Conlin, Rahul Gaur +8
Stellarator optimization often takes a two-stage approach, where in the first stage the boundary is varied in order to optimize for some physics metrics, while in the second stage…
Improving ideal MHD equilibrium accuracy with physics-informed neural networks
Timo Thun, Andrea Merlo, Rory Conlin +2
We present a novel approach to compute three-dimensional Magnetohydrodynamic equilibria by parametrizing Fourier modes with artificial neural networks and compare it to equilibria…
Numerical asymptotics of near-axis expansions of quasisymmetric magnetohydrostatic equilibria with anisotropic pressure
Lanke Fu, Eduardo Rodriguez, Rory Conlin +1
Quasisymmetry (QS) is a property of special magnetic configurations, where the magnetic field strength, but not necessarily the full vector field, has a direction of symmetry. QS l…
Extending near-axis equilibria in DESC
Dario Panici, Eduardo Rodriguez, Rory Conlin +2
The near-axis description of optimised stellarator fields has proven to be a powerful tool both for design and understanding of this magnetic confinement concept. The description c…
How does ion temperature gradient turbulence depend on magnetic geometry? Insights from data and machine learning
Matt Landreman, Jong Youl Choi, Caio Alves +4
Magnetic geometry has a significant effect on the level of turbulent transport in fusion plasmas. Here, we model and analyze this dependence using multiple machine learning methods…
High Order Free Boundary MHD Equilibria in DESC
Rory Conlin, Jonathan Schilling, Daniel W. Dudt +3
In this work we consider the free boundary inverse equilibrium problem for 3D ideal MHD. We review boundary conditions for both fixed and free boundary solutions and under what cir…
Spectrally accurate, reverse-mode differentiable bounce-averaging algorithm and its applications
Kaya Unalmis, Rahul Gaur, Rory Conlin +2
We present a fast, spectrally (exponentially) accurate, automatically differentiable bounce-averaging algorithm that is used to simplify kinetic models. Using this algorithm, imple…
Omnigenous stellarator equilibria with enhanced stability
Rahul Gaur, Rory Conlin, David Dickinson +7
To build an economically viable stellarator, it is essential to find a configuration that satisfies a set of favorable properties to achieve efficient steady-state nuclear fusion.…
ZERNIPAX: A Fast and Accurate Zernike Polynomial Calculator in Python
Yigit Gunsur Elmacioglu, Rory Conlin, Daniel W. Dudt +2
Zernike polynomials serve as an orthogonal basis on the unit disc, and have proven to be effective in optics simulations, astrophysics, and more recently in plasma simulations. Unl…
Stellarator Optimization with Constraints
Rory Conlin, Patrick Kim, Daniel W. Dudt +2
In this work we consider the problem of optimizing a stellarator subject to hard constraints on the design variables and physics properties of the equilibrium. We survey current nu…
Optimization of Nonlinear Turbulence in Stellarators
Patrick Kim, Stefan Buller, Rory Conlin +8
We present new stellarator equilibria that have been optimized for reduced turbulent transport using nonlinear gyrokinetic simulations within the optimization loop. The optimizatio…
Magnetic Fields with General Omnigenity
Daniel W. Dudt, Alan G. Goodman, Rory Conlin +2
Omnigenity is a desirable property of toroidal magnetic fields that ensures confinement of trapped particles. Confining charged particles is a basic requirement for any fusion powe…
Exploration via Planning for Information about the Optimal Trajectory
Viraj Mehta, Ian Char, Joseph Abbate +5
Many potential applications of reinforcement learning (RL) are stymied by the large numbers of samples required to learn an effective policy. This is especially true when applying…
Greedy permanent magnet optimization
Alan A. Kaptanoglu, Rory Conlin, Matt Landreman
A number of scientific fields rely on placing permanent magnets in order to produce a desired magnetic field. We have shown in recent work that the placement process can be formula…
Implementation of AI/Deep Learning Disruption Predictor into a Plasma Control System
William Tang, Ge Dong, Jayson Barr +17
This paper reports on advances to the state-of-the-art deep-learning disruption prediction models based on the Fusion Recurrent Neural Network (FRNN) originally introduced a 2019 N…
The DESC Stellarator Code Suite Part III: Quasi-symmetry optimization
Daniel Dudt, Rory Conlin, Dario Panici +1
The DESC stellarator optimization code takes advantage of advanced numerical methods to search the full parameter space much faster than conventional tools. Only a single equilibri…
The DESC Stellarator Code Suite Part I: Quick and accurate equilibria computations
Dario Panici, Rory Conlin, Daniel W. Dudt +2
3D equilibrium codes are vital for stellarator design and operation, and high-accuracy equilibria are also necessary for stability studies. This paper details comparisons of two th…