Divertor design through adjoint approaches and efficient code simulation strategies

Dekeyser, Wouter; Blommaert, Maarten; Ghoos, Kristel; Horsten, N.; Boerner, P.; Samaey, Giovanni; Baelmans, Martine

doi:10.1002/ctpp.201700199

Cited by 6 publications

(4 citation statements)

References 21 publications

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“…random proton paths through the phantom with vastly different WEPLs. This fact is also known from optimization studies concerning divertors in nuclear fusion reactors (Dekeyser et al 2018).…”

Section: Setup For Gatementioning

confidence: 80%

Exploration of differentiability in a proton computed tomography simulation framework

Aehle,

Alme,

Gábor Barnaföldi

et al. 2023

Phys. Med. Biol.

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Objective. Gradient-based optimization using algorithmic derivatives can be a useful technique to improve engineering designs with respect to a computer-implemented objective function. Likewise, uncertainty quantification through computer simulations can be carried out by means of derivatives of the computer simulation. However, the effectiveness of these techniques depends on how “well-linearizable” the software is. In this study, we assess how promising derivative information of a typical proton computed tomography (pCT) scan computer simulation is for the aforementioned applications. Approach. This study is mainly based on numerical experiments, in which we repeatedly evaluate three representative computational steps with perturbed input values. We support our observations with a review of the algorithmic steps and arithmetic operations performed by the software, using debugging techniques. Main results.The model-based iterative reconstruction (MBIR) subprocedure (at the end of the software pipeline) and the Monte Carlo (MC) simulation (at the beginning) were piecewise differentiable. However, the observed high density and magnitude of jumps was likely to preclude most meaningful uses of the derivatives. Jumps in the MBIR function arose from the discrete computation of the set of voxels intersected by a proton path, and could be reduced in magnitude by a “fuzzy voxels” approach. The investigated jumps in the MC function arose from local changes in the control flow that affected the amount of consumed random numbers. The tracking algorithm solves an inherently non-differentiable problem. Significance. Besides the technical challenges of merely applying AD to existing software projects, the MC and MBIR codes must be adapted to compute smoother functions. For the MBIR code, we presented one possible approach for this while for the MC code, this will be subject to further research. For the tracking subprocedure, further research on surrogate models is necessary.

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Section: Setup For Gatementioning

confidence: 80%

Exploration of differentiability in a proton computed tomography simulation framework

Aehle,

Alme,

Gábor Barnaföldi

et al. 2023

Phys. Med. Biol.

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“…This introduces statistical noise in the simulation chain, hampering gradient's accuracy. The discrete adjoint method has proven robust in case of statistical noise, albeit in a simplied 1D setting, by ensuring exact correlation between the particle trajectories of primal and adjoint simulations [58]. However, correlation in higher dimensional settings is hard to maintain.…”

Section: Discussionmentioning

confidence: 99%

Algorithmic Differentiation for adjoint sensitivity calculation in plasma edge codes

Carli,

Hascoët,

Dekeyser

et al. 2023

Journal of Computational Physics

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“…parallel writing by multiple cores. Also the accurate computation of sensitivities in the presence of MC noise (adjoint approach) has been demonstrated [43], and will be pursued in further EIRENE development involving algorithmic differentiation as shown in [41] for the (deterministic) plasma solver within SOLPS-ITER.…”

Section: Discussionmentioning

confidence: 99%

Fluid, kinetic and hybrid approaches for neutral and trace ion edge transport modelling in fusion devices

et al. 2022

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Neutral gas physics and neutral interactions with the plasma are key aspects of edge plasma and divertor physics in a fusion reactor including the detachment phenomenon often seen as key to dealing with the power exhaust challenges. A full physics description of the neutral gas dynamics requires a 6D kinetic approach, potentially time dependent, where the details of the wall geometry play a substantial role, to the extent that, e.g., the subdivertor region has to be included. The Monte Carlo (MC) approach used for about 30 years in EIRENE [1], is well suited to solve these types of complex problems. Indeed, the MC approach allows simulating the 6D kinetic equation without having to store the velocity distribution on a 6D grid, at the cost of introducing statistical noise. MC also provides very good flexibility in terms of geometry and atomic and molecular (A&M) processes. However, it becomes computationally extremely demanding in high-collisional regions (HCR) as anticipated in ITER and DEMO. Parallelization on particles helps reducing the simulation wall clock time, but to provide speed-up in situations where single trajectories potentially involve a very large number of A&M events, it is important to derive a hierarchy of models in terms of accuracy and to clearly identify for what type of physics issues they provide reliable answers. It was demonstrated that advanced fluid neutral (AFN) models are very accurate in HCRs, and at least an order of magnitude faster than fully kinetic simulations. Based on these fluid models, three hybrid fluid-kinetic approaches are introduced: a spatially hybrid technique (SpH), a micro-Macro hybrid method (mMH), and an asymptotic-preserving MC (APMC) scheme, to combine the efficiency of a fluid model with the accuracy of a kinetic description. In addition, atomic and molecular ions involved in the edge plasma chemistry can also be treated kinetically within the MC solver, opening the way for further hybridisation by enabling kinetic impurity ion transport calculations. This paper aims to give an overview of methods mentioned and suggests the most prospective combinations to be developed.

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Divertor design through adjoint approaches and efficient code simulation strategies

Cited by 6 publications

References 21 publications

Exploration of differentiability in a proton computed tomography simulation framework

Exploration of differentiability in a proton computed tomography simulation framework

Algorithmic Differentiation for adjoint sensitivity calculation in plasma edge codes

Fluid, kinetic and hybrid approaches for neutral and trace ion edge transport modelling in fusion devices

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