A Possible Method of Carbon Deposit Mapping on Plasma Facing Components Using Infrared Thermography

• URL: http://arxiv.org/abs/2010.06374v1
• Date: Fri, 25 Sep 2020 12:04:50 GMT
• Title: A Possible Method of Carbon Deposit Mapping on Plasma Facing Components Using Infrared Thermography
• Authors: R Mitteau (IRFM), J Spruytte (IRFM), S Vallet (IRFM), J Trav\`ere (IRFM), D Guilhem (IRFM), C Brosset (IRFM)
• Abstract summary: The material eroded from the surface of plasma facing components is redeposited partly close to high heat flux areas. The mapping of the deposit is still a matter of intense scientific activity, especially during the course of experimental campaigns. A method based on the comparison of surface temperature maps, obtained in situ by infrared cameras and by theoretical modelling is proposed.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The material eroded from the surface of plasma facing components is redeposited partly close to high heat flux areas. At these locations, the deposit is heated by the plasma and the deposition pattern evolves depending on the operation parameters. The mapping of the deposit is still a matter of intense scientific activity, especially during the course of experimental campaigns. A method based on the comparison of surface temperature maps, obtained in situ by infrared cameras and by theoretical modelling is proposed. The difference between the two is attributed to the thermal resistance added by deposited material, and expressed as a deposit thickness. The method benefits of elaborated imaging techniques such as possibility theory and fuzzy logics. The results are consistent with deposit maps obtained by visual inspection during shutdowns.

Related papers

• Dual Band Video Thermography Near Ambient Conditions [16.03898251374111]
  Long-wave infrared radiation captured by a thermal camera consists of two components: (a) light from the environment reflected or transmitted by a surface, and (b) light emitted by the surface after undergoing heat transport through the object and exchanging heat with the surrounding environment.<n>We introduce the first method that separates reflected and emitted components of light in videos captured by two thermal cameras with different spectral sensitivities.<n>We derive a dual-band thermal image formation model and develop algorithms to estimate the surface's emissivity and its time-varying temperature while isolating a dynamic background.
  arXiv  Detail & Related papers  (2025-09-14T16:21:29Z)
• Topological Materials for Near-Field Radiative Heat Transfer [0.848093199044277]
  Topological materials can carry quantum states and electromagnetic energy, benefiting nanolasers or quantum photonic systems. Near-field thermal radiation in subwavelength systems supporting surface modes has various applications, including nanoscale thermal management and energy conversion. We present various topological effects, such as periodic and quasi-periodic nanoparticle arrays, Dirac and Weyl semimetal-based materials, structures with broken global symmetries, and other topological insulators, on near-field heat transfer.
  arXiv  Detail & Related papers  (2024-06-06T08:49:57Z)
• TCI-Former: Thermal Conduction-Inspired Transformer for Infrared Small Target Detection [58.00308680221481]
  Infrared small target detection (ISTD) is critical to national security and has been extensively applied in military areas. Most ISTD networks focus on designing feature extraction blocks or feature fusion modules, but rarely describe the ISTD process from the feature map evolution perspective. We propose Thermal Conduction-Inspired Transformer (TCI-Former) based on the theoretical principles of thermal conduction.
  arXiv  Detail & Related papers  (2024-02-03T05:51:22Z)
• Absorption-Based, Passive Range Imaging from Hyperspectral Thermal Measurements [6.719751155411075]
  We introduce a novel passive range imaging method based on atmospheric absorption of ambient thermal radiance. Range features from 15m to 150m are recovered, with good qualitative match to unaligned lidar data.
  arXiv  Detail & Related papers  (2023-08-10T18:35:22Z)
• Learning Structure-Guided Diffusion Model for 2D Human Pose Estimation [71.24808323646167]
  We propose textbfDiffusionPose, a new scheme for learning keypoints heatmaps by a neural network. During training, the keypoints are diffused to random distribution by adding noises and the diffusion model learns to recover ground-truth heatmaps from noised heatmaps. Experiments show the prowess of our scheme with improvements of 1.6, 1.2, and 1.2 mAP on widely-used COCO, CrowdPose, and AI Challenge datasets.
  arXiv  Detail & Related papers  (2023-06-29T16:24:32Z)
• Precise Facial Landmark Detection by Reference Heatmap Transformer [52.417964103227696]
  We propose a novel Reference Heatmap Transformer (RHT) for more precise facial landmark detection. The experimental results from challenging benchmark datasets demonstrate that our proposed method outperforms the state-of-the-art methods in the literature.
  arXiv  Detail & Related papers  (2023-03-14T12:26:48Z)
• Lock-in thermography using diamond quantum sensors [0.0]
  We demonstrate lock-in thermography using nitrogen-vacancy centers in diamond nanoparticles. We successfully visualize thermal diffusion in glass coverslip and Teflon with micrometer resolution.
  arXiv  Detail & Related papers  (2022-12-15T04:57:21Z)
• Does Thermal Really Always Matter for RGB-T Salient Object Detection? [153.17156598262656]
  This paper proposes a network named TNet to solve the RGB-T salient object detection (SOD) task. In this paper, we introduce a global illumination estimation module to predict the global illuminance score of the image. On the other hand, we introduce a two-stage localization and complementation module in the decoding phase to transfer object localization cue and internal integrity cue in thermal features to the RGB modality.
  arXiv  Detail & Related papers  (2022-10-09T13:50:12Z)
• Unsupervised Discovery of Inertial-Fusion Plasma Physics using Differentiable Kinetic Simulations and a Maximum Entropy Loss Function [77.34726150561087]
  We create a differentiable solver for the plasma kinetics 3D partial-differential-equation and introduce a domain-specific objective function. We apply this framework to an inertial-fusion relevant configuration and find that the optimization process exploits a novel physical effect.
  arXiv  Detail & Related papers  (2022-06-03T15:27:33Z)
• Hierarchical Temperature Imaging Using Pseudo-Inversed Convolutional Neural Network Aided TDLAS Tomography [16.39189394591311]
  Convolutional Neural Networks (CNNs) have been proofed to be more robust and accurate for image reconstruction. We propose a Pseudo-Inversed CNN (PI-CNN) for hierarchical temperature imaging.
  arXiv  Detail & Related papers  (2021-06-05T14:14:41Z)
• Photothermal-SR-Net: A Customized Deep Unfolding Neural Network for Photothermal Super Resolution Imaging [9.160910754837756]
  Photothermal-SR-Net is proposed in this paper, which performs deconvolution by deep unfolding considering the underlying physics. Photothermal-SR-Net applies trained block-sparsity thresholding to the acquired thermal images in each convolutional layer.
  arXiv  Detail & Related papers  (2021-04-21T14:41:04Z)
• Multi-Scale Thermal to Visible Face Verification via Attribute Guided Synthesis [55.29770222566124]
  We use attributes extracted from visible images to synthesize attribute-preserved visible images from thermal imagery for cross-modal matching. A novel multi-scale generator is proposed to synthesize the visible image from the thermal image guided by the extracted attributes. A pre-trained VGG-Face network is leveraged to extract features from the synthesized image and the input visible image for verification.
  arXiv  Detail & Related papers  (2020-04-20T01:45:05Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.