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Alan Kaptanoglu

Publications and source records attributed to Alan Kaptanoglu.

4 recordsLinked to original sources

Computational boundary specification in 3D fixed-boundary magnetohydrodynamic equilibrium modeling

Outside the core of the plasma, the plasma current and pressure rapidly transition to zero in a scrape-off or edge region or plasma-vacuum interface. However, existing tools for fixed-boundary magnetohydrodynamic equilibria in 2D and 3D domains $\Omega$ typically prescribe the computational boundary $\partial\Omega$ interior to this transition layer. We (1) argue that a more realistic and robust assumption is to define the computational boundary exterior to this transition layer, in a vacuum-like region where $J|_{\partial\Omega} \sim p|_{\partial\Omega} \sim 0$, (2) show that, without this boundary change, existing coil optimization routines for 3D toroidal equilibria (stellarators) should be changed to match free-boundary equilibrium requirements, and (3) derive an algorithm for a fixed-boundary 3D equilibrium solver compatible with a very general computational boundary, with conditions $B \cdot n|_{\partial\Omega} \neq 0$ (not necessarily a flux surface), $p|_{\partial\Omega} \neq \text{const.}$ (not necessarily an isobar), and $J \times n|_{\partial\Omega} \neq 0$.

physics.plasm-ph

A flexible and differentiable coil proxy for stellarator equilibrium optimization

Balancing plasma performance and coil cost is a significant challenge when designing a stellarator power plant. Most current stellarator designs are produced through two-stage optimization: stage-1 for the equilibrium and stage-2 for a coil design that reproduces its magnetic configuration. Because few proxies connect both stages, two-stage optimization can produce plasmas that have high-quality physical properties but overly complex coils. In recent years, single-stage optimization has increasingly been used to optimize the plasma and coils simultaneously in order to improve the plasma-coil balance. However, all existing single-stage tools are specialized for filament coils, cannot model coil systems containing permanent magnets (PM) or dipole arrays, and continue to be challenged by numerical problems. The quasi-single-stage (QSS) optimization finds a middle-ground by integrating a coil optimization subproblem into stage-1 optimization. We present a flexible, differentiable coil complexity proxy based on the newly developed QUADCOIL coil optimization code. QUADCOIL is fast and can target realistic coil metrics and constraints that are unavailable to codes with comparable speed. We demonstrate the effectiveness and flexibility of the QUADCOIL proxy by presenting two QSS optimization studies. The first study produces a permanent magnet solution for the MUSE stellarator with 29% fewer magnets than previous solutions. The second study produces a coil solution for the ARIES-CS stellarator with 27% reductions in both peak and root-mean-square force.

physics.plasm-ph

Electromagnetic coil optimization for reduced Lorentz forces

The reduction of magnetic forces on electromagnetic coils is an important consideration in the design of high-field devices such as the stellarator or tokamak. Unfortunately, these forces may be too time-consuming to evaluate by conventional finite element modeling within an optimization loop. Although mutual forces can be computed rapidly by approximating large-bore coils as infinitely thin, this approximation does not hold for self-forces as it leads to an unphysical divergence. Recently, a novel reduced model for the self-field, self-force, and self-inductance of electromagnetic coils based on filamentary models was rigorously derived and demonstrated to be highly accurate and numerically efficient to evaluate. In this paper, we present an implementation of the reduced self-force model employing automatic differentiation within the SIMSOPT stellarator design software and use it in derivative-based coil optimization for a quasi-axisymmetric stellarator. We show that it is possible to significantly reduce point-wise forces throughout the coils, though this comes with trade-offs to fast particle losses and the minimum distance between coils and the plasma surface. The trade-off between magnetic forces and coil-surface distance is mediated by the minimum coil-coil distance for coils near the inboard side of the "bean" cross-section of the plasma. The relationship between forces and fast particle losses is mediated by the normal field error. Coil forces can be lowered to a threshold with minimal deterioration to losses. Importantly, the magnet optimization approach here can be used also for tokamaks, other fusion concepts, and applications outside of fusion.

physics.plasm-ph

Extending the trapping theorem to provide local stability guarantees for quadratically nonlinear models

The Navier Stokes equations (NSEs) are partial differential equations (PDEs) to describe the nonlinear convective motion of fluids and they are computationally expensive to simulate because of their high nonlinearity and variables being fully coupled. Reduced-order models (ROMs) are simpler models for evolving the flows by capturing only the dominant behaviors of a system and can be used to design controllers for high-dimensional systems. However it is challenging to guarantee the stability of these models either globally or locally. Ensuring the stability of ROMs can improve the interpretability of the behavior of the dynamics and help develop effective system control strategies. For quadratically nonlinear systems that represent many fluid flows, the Schlegel and Noack trapping theorem (JFM, 2015) can be used to check if ROMs are globally stable (long-term bounded). This theorem was subsequently incorporated into system identification techniques that determine models directly from data. In this work, we relax the quadratically energy-preserving constraints in this theorem, and then promote local stability in data-driven models of quadratically nonlinear dynamics. First, we prove a theorem outlining sufficient conditions to ensure local stability in linear-quadratic systems and provide an estimate of the stability radius. Second, we incorporate this theorem into system identification methods and produce a-priori locally stable data-driven models. Several examples are presented to demonstrate the effectiveness and accuracy of the proposed algorithm.

physics.comp-ph