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The shape gradient quantifies the change in some figure of merit resulting from differential perturbations to a shape. Shape gradients can be applied to gradient-based optimization, sensitivity analysis, and tolerance calculation. An…

等离子体物理 · 物理学 2019-04-10 Thomas Antonsen, , Elizabeth J. Paul , Matt Landreman

Using recently developed adjoint methods for computing the shape derivatives of functions that depend on MHD equilibria (Antonsen et al. 2019; Paul et al. 2020), we present the first example of analytic gradient-based optimization of…

等离子体物理 · 物理学 2021-04-21 Elizabeth Paul , Matt Landreman , Thomas Antonsen

The design of a stellarator with acceptable confinement properties requires optimization of the magnetic field in the non-convex, high-dimensional spaces describing their geometry. Another major challenge facing the stellarator program is…

等离子体物理 · 物理学 2020-05-18 Elizabeth Paul

Tight tolerances have been a leading driver of cost in recent stellarator experiments, so improved definition and control of tolerances can have significant impact on progress in the field. Here we relate tolerances to the shape gradient…

等离子体物理 · 物理学 2018-03-09 Matt Landreman , Elizabeth J Paul

Optimizing shapes and topology of physical devices is crucial for both scientific and technological advancements, given its wide-ranging implications across numerous industries and research areas. Innovations in shape and topology…

计算物理 · 物理学 2023-10-02 Alexander Luce , Rasoul Alaee , Fabian Knorr , Florian Marquardt

Stellarators are a promising route to steady-state fusion power. However, to achieve the required confinement, the magnetic geometry must be highly optimized. This optimization requires navigating high-dimensional spaces, often…

等离子体物理 · 物理学 2019-09-25 Elizabeth Paul , Ian Abel , Matt Landreman , William Dorland

A gradient-based method for shape optimization problems constrained by the acoustic wave equation is presented. The method makes use of high-order accurate finite differences with summation-by-parts properties on multiblock curvilinear…

数值分析 · 数学 2024-05-09 Gustav Eriksson , Vidar Stiernström

As more and more multiphysics effects are entering the field of CFD simulations, this raises the question how they can be accurately captured in gradient computations for shape optimization. The latter has been successfully enriched over…

计算物理 · 物理学 2018-11-02 Ole Burghardt , Nicolas R. Gauger

An adjoint method to calculate the gradient of island width in stellarators is presented and applied to a set of magnetic field configurations. The underlying method of calculation of the island width is that of Cary & Hanson (1991) (with a…

等离子体物理 · 物理学 2021-05-19 Alessandro Geraldini , Matt Landreman , Elizabeth Paul

For a given {\it misfit function}, a specified optimality measure of a model, its gradient describes the manner in which one may alter properties of the system to march towards a stationary point. The adjoint method, arising from…

太阳与恒星天体物理 · 物理学 2015-05-28 Shravan Hanasoge , Aaron Birch , Laurent Gizon , Jeroen Tromp

We present a method for stellarator coil design via gradient-based optimization of the coil-winding surface. The REGCOIL (Landreman 2017 Nucl. Fusion 57 046003) approach is used to obtain the coil shapes on the winding surface using a…

等离子体物理 · 物理学 2018-07-04 E. J. Paul , M. Landreman , A. Bader , W. Dorland

This work presents a partitioned solution procedure to compute shape gradients in fluid-structure interaction (FSI) using black-box adjoint solvers. Special attention is paid to project the gradients onto the undeformed configuration. This…

The adjoint sensitivity method scalably computes gradients of solutions to ordinary differential equations. We generalize this method to stochastic differential equations, allowing time-efficient and constant-memory computation of gradients…

机器学习 · 计算机科学 2020-10-20 Xuechen Li , Ting-Kam Leonard Wong , Ricky T. Q. Chen , David Duvenaud

This paper develops a framework connecting discrete adjoint gradient-error analysis with an optimization method that uses directional error tolerances, and applies it to airfoil shape optimization governed by a conservative full-potential…

最优化与控制 · 数学 2026-05-19 Humberto Gimenes Macedo , Luís Felipe Bueno

Adjoint methods can speed up stellarator optimisation by providing gradient information more efficiently compared to finite-difference evaluations. Adjoint methods are herein applied to vacuum magnetic fields, with objective functions…

等离子体物理 · 物理学 2022-02-16 Richard Nies , Elizabeth J. Paul , Stuart R. Hudson , Amitava Bhattacharjee

This paper proposes a new approach for the calibration of material parameters in local elastoplastic constitutive models. The calibration is posed as a constrained optimization problem, where the constitutive model evolution equations for a…

计算工程、金融与科学 · 计算机科学 2025-05-09 Ryan Yan , D. Thomas Seidl , Reese E. Jones , Panayiotis Papadopoulos

In the optimization of turbomachinery components, shape sensitivities for fluid dynamical objective functions have been used for a long time. As peak stress is not a differential func- tional of the shape, such highly efficient procedures…

The sharp increasing in fabrication capabilities of nanomaterials, and complex structures such as meta-surfaces and metalens, has opened to the possibility of employing them for accurately control the electromagnetic field, beyond the…

数值分析 · 数学 2026-03-17 Vincenzo Mottola , Luisa Faella , Carlo Forestiere , Antonello Tamburrino

A direct construction of equilibrium magnetic fields with toroidal topology at arbitrary order in the distance from the magnetic axis is carried out, yielding an analytical framework able to explore the landscape of possible magnetic flux…

等离子体物理 · 物理学 2020-01-29 R. Jorge , W. Sengupta , M. Landreman

Coil complexity is a critical consideration in stellarator design. The traditional two-step optimization approach, in which the plasma boundary is optimized for physics properties and the coils are subsequently optimized to be consistent…

等离子体物理 · 物理学 2021-04-26 Arthur Carlton-Jones , Elizabeth J. Paul , William Dorland
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