arXiv subjects

D. Hamm

Publications and source records attributed to D. Hamm.

6 recordsLinked to original sources

arXiv2026

High-power TCV scenario for conventional and alternative divertor studies

Alternative divertor configurations (ADCs) must be evaluated under boundary plasma conditions approaching reactor-level values to be considered a reliable, physics-based solution for tokamak power exhaust. Most ADC experiments performed to date were at relatively low exhaust power. This work presents a high-power scenario on the TCV tokamak enabling the study of a wide variety of divertor magnetic shapes under an expanded SOL and power exhaust parameter space. The scenario is characterized by high power levels of electron cyclotron resonance heating ($2.5\,\text{MW}$ fully absorbed in a $\sim1\,\text{m}^{3}$ plasma) at high plasma current (edge safety factor $q_{95}\approx 2.5$), and low upstream separatrix densities ($n_{e,\text{u}}\approx1\times10^{19}\,\text{m}^{-3}$, Greenwald fraction $f_{\text{G}}\approx 0.1$). Stationary parallel heat fluxes up to $100\,\text{MW m}^{-2}$ are measured at the divertor target, an order of magnitude above previous TCV power exhaust studies. The obtained SOL collisionality and Lengyel detachment scaling metric lie within range of values expected in future reactors (SPARC, ITER, ARC).

physics.plasm-ph↗

arXiv2026

Synthetic Diagnostic Modeling for Plasma Tomography: Geometry Matrix Computation Methods and Impact of Model Accuracy

Tomographic emissivity reconstruction from plasma diagnostics data relies on a synthetic model mapping the plasma emissivity to the measured signals. The model, referred to as a geometry matrix in the plasma imaging community, is often built using the line-of-sight (LoS) approximation. This approximation neglects the finite width of the detector viewing beams and can therefore introduce systematic errors. Physically correct volume-of-sight (VoS) models remove this inaccuracy by accounting for the full 3D extent of the viewing beams. Their adoption, however, is sometimes hindered by the difficulty of independently validating them. We present an intuitive and easily inspectable voxel-to-detector (V2D) approach for computing physically accurate VoS geometry matrices, based on discretizing the tokamak vessel into voxels and estimating the contribution of each voxel to the measurements of each detector. We apply the V2D approach to the soft X-ray (SXR) and bolometry systems of the TCV tokamak. Through phantom-based studies on physically realistic emissivity profiles, we quantify the improvement in reconstruction quality obtained by using VoS rather than LoS models. We find that the VoS model yields overall better accuracy and precision; however, interestingly, the simpler LoS model does not introduce a significant systematic bias in the estimated total, core, divertor and main chamber radiated powers. We further compare the V2D geometry matrix with an independent ray-tracing implementation, finding excellent agreement that validates both approaches for routine use at TCV. All routines developed in this work are made openly available.

physics.plasm-ph↗

arXiv2026

Real-time Tomography-based Bayesian Inference from TCV Bolometry Data

Radiated power information is crucial to diagnose and optimize the performance of fusion plasmas. Traditionally, at the TCV tokamak, radiated power analysis has only ever been possible following plasma discharge termination. However, recently, TCV bolometer data have become available in real-time. This offers the opportunity of integrating the radiated power information into the TCV plasma control system. In this work, we propose a novel real-time tomography-based Bayesian technique allowing estimation of the power radiated from user-defined regions of interest in the plasma. The real-time estimates are obtained as computationally cheap linear combinations of bolometer measurements, using pre-computed coefficients that are optimized for the specific discharge planned. This method is not, thus, trained on a set of synthetic or tomographically reconstructed emissivity profiles. We detail the derivation of the technique and show its equivalence to traditional tomographic estimates under suitable conditions. We then demonstrate that this technique enables accurate real-time estimation of the total, core, divertor and main chamber radiated power, by its application to a representative and heterogeneous set of TCV discharges. Finally, we discuss the robustness of the technique to faulty detectors, showing that simple precautions allow safe handling of many common issues. The computational routines implementing the described technique are provided as open-source code.

physics.plasm-ph↗

arXiv2026

Non-dimensional confinement scaling in similar negative triangularity plasmas on the DIII-D and TCV tokamaks

Similarity experiments were performed on the DIII-D and TCV tokamaks to explore the scaling of energy confinement in negative triangularity plasmas using non-dimensional variables. Near up-down symmetric plasmas with large top-bottom averaged negative triangularity were created in a lower single null configuration, with the shape of the separatrix being closely matched between the two devices. The normalized energy confinement is found to weakly improve at increasing collisionality and, between the two devices, shows a machine size scaling behavior between Bohm and gyro-Bohm. Engineering scaling on a large DIII-D dataset is in agreement with the non-dimensional experiment.

physics.plasm-ph↗

arXiv2025

Tomography for Plasma Imaging: a Unifying Framework for Bayesian Inference

Plasma diagnostics often employ computerized tomography to estimate emissivity profiles from a finite, and often limited, number of line-integrated measurements. Decades of algorithmic refinement have brought considerable improvements, and led to a variety of employed solutions. These often feature an underlying, common structure that is rarely acknowledged or investigated. In this paper, we present a unifying perspective on sparse-view tomographic reconstructions for plasma imaging, highlighting how many inversion approaches reported in the literature can be naturally understood within a Bayesian framework. In this setting, statistical modelling of acquired data leads to a likelihood term, while the assumed properties of the profile to be reconstructed are encoded within a prior term. Together, these terms yield the posterior distribution, which models all the available information on the profile to be reconstructed. We show how credible reconstructions, uncertainty quantification and further statistical quantities of interest can be efficiently obtained from noisy tomographic data by means of a stochastic gradient flow algorithm targeting the posterior. This is demonstrated by application to soft x-ray imaging at the TCV tokamak. We validate the proposed imaging pipeline on a large dataset of generated model phantoms, showing how posterior-based inference can be leveraged to perform principled statistical analysis of quantities of interest. Finally, we address some of the inherent, and thus remaining, limitations of sparse-view tomography. All the computational routines used in this work are made available as open access code.

physics.plasm-ph↗

arXiv2017

The KDK (potassium decay) experiment

Potassium-40 (${}^{40}$K) is a background in many rare-event searches and may well play a role in interpreting results from the DAMA dark-matter search. The electron-capture decay of ${}^{40}$K to the ground state of ${}^{40}$Ar has never been measured and contributes an unknown amount of background. The KDK (potassium decay) collaboration will measure this branching ratio using a ${}^{40}$K source, an X-ray detector, and the Modular Total Absorption Spectrometer at Oak Ridge National Laboratory.

nucl-ex↗