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Keywords = Ennerdale

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26 pages, 5962 KiB  
Review
Resurgence of a Nation’s Radiation Science Driven by Its Nuclear Industry Needs
by Laura Leay, Aliaksandr Baidak, Christopher Anderson, Choen May Chan, Aaron Daubney, Thomas Donoclift, Gemma Draper, Ruth Edge, Jeff Hobbs, Luke Jones, Nicholas J. S. Mason, Darryl Messer, Mel O’Leary, Robin Orr, Simon M. Pimblott, Samir de Moraes Shubeita, Andrew D. Smith, Helen Steele, Paul Wady and Frederick Currell
Appl. Sci. 2021, 11(23), 11081; https://doi.org/10.3390/app112311081 - 23 Nov 2021
Cited by 2 | Viewed by 2588
Abstract
This article describes the radiation facilities and associated sample preparation, management, and analysis equipment currently in place at the Dalton Cumbrian Facility, a facility which opened in 2011 to support the UK’s nuclear industry. Examples of measurements performed using these facilities are presented [...] Read more.
This article describes the radiation facilities and associated sample preparation, management, and analysis equipment currently in place at the Dalton Cumbrian Facility, a facility which opened in 2011 to support the UK’s nuclear industry. Examples of measurements performed using these facilities are presented to illustrate their versatility and the breadth of research they make possible. Results are presented from research which furthers our understanding of radiation damage to polymeric materials, radiolytic yield of gaseous products in situations relevant to nuclear materials, radiation chemistry in light water reactor cooling systems, material chemistry relevant to immobilization of nuclear waste, and radiation-induced corrosion of fuel cladding elements. Applications of radiation chemistry relevant to health care are also described. Research concerning the mechanisms of radioprotection by dietary carotenoids is reported. An ongoing open-labware project to develop a suite of modular sample handling components suited to radiation research is described, as is the development of a new neutron source able to provide directional beams of neutrons. Full article
(This article belongs to the Special Issue Applied Radiation Chemistry: Theory, Methods and Applications)
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6338 KiB  
Technical Note
Ground-Control Networks for Image Based Surface Reconstruction: An Investigation of Optimum Survey Designs Using UAV Derived Imagery and Structure-from-Motion Photogrammetry
by Toby N. Tonkin and Nicholas G. Midgley
Remote Sens. 2016, 8(9), 786; https://doi.org/10.3390/rs8090786 - 21 Sep 2016
Cited by 217 | Viewed by 13493
Abstract
The use of small UAV (Unmanned Aerial Vehicle) and Structure-from-Motion (SfM) with Multi-View Stereopsis (MVS) for acquiring survey datasets is now commonplace, however, aspects of the SfM-MVS workflow require further validation. This work aims to provide guidance for scientists seeking to adopt this [...] Read more.
The use of small UAV (Unmanned Aerial Vehicle) and Structure-from-Motion (SfM) with Multi-View Stereopsis (MVS) for acquiring survey datasets is now commonplace, however, aspects of the SfM-MVS workflow require further validation. This work aims to provide guidance for scientists seeking to adopt this aerial survey method by investigating aerial survey data quality in relation to the application of ground control points (GCPs) at a site of undulating topography (Ennerdale, Lake District, UK). Sixteen digital surface models (DSMs) were produced from a UAV survey using a varying number of GCPs (3-101). These DSMs were compared to 530 dGPS spot heights to calculate vertical error. All DSMs produced reasonable surface reconstructions (vertical root-mean-square-error (RMSE) of <0.2 m), however, an improvement in DSM quality was found where four or more GCPs (up to 101 GCPs) were applied, with errors falling to within the suggested point quality range of the survey equipment used for GCP acquisition (e.g., vertical RMSE of <0.09 m). The influence of a poor GCP distribution was also investigated by producing a DSM using an evenly distributed network of GCPs, and comparing it to a DSM produced using a clustered network of GCPs. The results accord with existing findings, where vertical error was found to increase with distance from the GCP cluster. Specifically vertical error and distance to the nearest GCP followed a strong polynomial trend (R2 = 0.792). These findings contribute to our understanding of the sources of error when conducting a UAV-SfM survey and provide guidance on the collection of GCPs. Evidence-driven UAV-SfM survey designs are essential for practitioners seeking reproducible, high quality topographic datasets for detecting surface change. Full article
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