arXiv subjects

Chris Walsh

Publications and source records attributed to Chris Walsh.

6 recordsLinked to original sources

arXiv2024

Kinetic Corrections to Heat-flow and Nernst advection for Laser Heated Plasmas

Reduced models for approximating the impact of kinetic electron behavior on the transport of thermal energy and magnetic field are investigated. The thermal flux limiter has improved agreement with Vlasov-Fokker-Planck data when a harmonic form is used that adjusts the electron mean free path to account for electron-electron collisions; these results apply to both unmagnetized and magnetized plasmas. Once a magnetic field is incorporated, the mean free path should also be modified using the electron gyroradius. A flux limiter on Nernst advection of magnetic field is also required; a form that limits Nernst by the same fraction as the thermal heat-flow best reproduces kinetic simulations. A flux limiter form for the cross terms (Righi-Leduc and cross-gradient-Nernst) are also suggested. Hohlraum simulations relevant to fusion experiments on the National Ignition Facility are found to be sensitive to all of these details.

physics.plasm-ph↗

arXiv2024

Synthetic Privileged Information Enhances Medical Image Representation Learning

Multimodal self-supervised representation learning has consistently proven to be a highly effective method in medical image analysis, offering strong task performance and producing biologically informed insights. However, these methods heavily rely on large, paired datasets, which is prohibitive for their use in scenarios where paired data does not exist, or there is only a small amount available. In contrast, image generation methods can work well on very small datasets, and can find mappings between unpaired datasets, meaning an effectively unlimited amount of paired synthetic data can be generated. In this work, we demonstrate that representation learning can be significantly improved by synthetically generating paired information, both compared to training on either single-modality (up to 4.4x error reduction) or authentic multi-modal paired datasets (up to 5.6x error reduction).

cs.CV↗

arXiv2022

2020 CATARACTS Semantic Segmentation Challenge

Surgical scene segmentation is essential for anatomy and instrument localization which can be further used to assess tissue-instrument interactions during a surgical procedure. In 2017, the Challenge on Automatic Tool Annotation for cataRACT Surgery (CATARACTS) released 50 cataract surgery videos accompanied by instrument usage annotations. These annotations included frame-level instrument presence information. In 2020, we released pixel-wise semantic annotations for anatomy and instruments for 4670 images sampled from 25 videos of the CATARACTS training set. The 2020 CATARACTS Semantic Segmentation Challenge, which was a sub-challenge of the 2020 MICCAI Endoscopic Vision (EndoVis) Challenge, presented three sub-tasks to assess participating solutions on anatomical structure and instrument segmentation. Their performance was assessed on a hidden test set of 531 images from 10 videos of the CATARACTS test set.

eess.IV↗

arXiv2019

Modification of classical electron transport due to collisions between electrons and fast ions

A Fokker-Planck model for the interaction of fast ions with the thermal electrons in a quasi-neutral plasma is developed. When the fast ion population has a net flux (i.e. the distribution of the fast ions is anisotropic in velocity space) the electron distribution function is significantly perturbed from Maxwellian by collisions with the fast ions, even if the fast ion density is orders of magnitude smaller than the electron density. The Fokker-Planck model is used to derive classical electron transport equations (a generalized Ohm's law and a heat flow equation) that include the effects of the electron-fast ion collisions. It is found that these collisions result in a current term in the transport equations which can be significant even when total current is zero. The new transport equations are analyzed in the context of a number of scenarios including $α$ particle heating in ICF and MIF plasmas and ion beam heating of dense plasmas.

physics.plasm-ph↗

arXiv2019

Synthetic Nuclear Diagnostics for Inferring Plasma Properties of Inertial Confinement Fusion Implosions

A suite of synthetic nuclear diagnostics has been developed to post-process radiation hydrodynamics simulations performed with the code Chimera. These provide experimental observables based on simulated capsule properties and are used to assess alternative experimental and data analysis techniques. These diagnostics include neutron spectroscopy, primary and scattered neutron imaging, neutron activation, $γ$-ray time histories and carbon $γ$-ray imaging. Novel features of the neutron spectrum have been analysed to infer plasma parameters. The nT and nD backscatter edges have been shown to provide a shell velocity measurement. Areal density asymmetries created by low mode perturbations have been inferred from the slope of the downscatter spectrum down to 10 MeV. Neutron activation diagnostics showed significant aliasing of high mode areal density asymmetries when observing a capsule implosion with 3D multimode perturbations applied. Carbon $γ$-ray imaging could be used to image the ablator at high convergence ratio. Time histories of both the fusion and carbon $γ$ signals showed a greater time difference between peak intensities for the perturbed case when compared to a symmetric simulation.

physics.plasm-ph↗

arXiv2018

The Dynamic Bowser Routing Problem

We investigate opportunities offered by telematics and analytics to enable better informed, and more integrated, collaborative management decisions on construction sites. We focus on efficient refuelling of assets across construction sites. More specifically, we develop decision support models that, by leveraging data supplied by different assets, schedule refuelling operations by minimising the distance travelled by the bowser truck as well as fuel shortages. Motivated by a practical case study elicited in the context of a project we recently conducted at Crossrail, we introduce the Dynamic Bowser Routing Problem. In this problem the decision maker aims to dynamically refuel, by dispatching a bowser truck, a set of assets which consume fuel and whose location changes over time; the goal is to ensure that assets do not run out of fuel and that the bowser covers the minimum possible distance. We investigate deterministic and stochastic variants of this problem and introduce effective and scalable mathematical programming models to tackle these cases. We demonstrate the effectiveness of our approaches in the context of an extensive computational study designed around data collected on site as well as supplied by our project partners. Keywords: Routing; Dynamic Bowser Routing Problem; Stochastic Bowser Routing Problem; Mixed-Integer Linear Programming; Construction.

math.OC↗