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- Murari, A., et al.
(författare)
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A control oriented strategy of disruption prediction to avoid the configuration collapse of tokamak reactors
- 2024
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Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 15:1
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Tidskriftsartikel (refereegranskat)abstract
- The objective of thermonuclear fusion consists of producing electricity from the coalescence of light nuclei in high temperature plasmas. The most promising route to fusion envisages the confinement of such plasmas with magnetic fields, whose most studied configuration is the tokamak. Disruptions are catastrophic collapses affecting all tokamak devices and one of the main potential showstoppers on the route to a commercial reactor. In this work we report how, deploying innovative analysis methods on thousands of JET experiments covering the isotopic compositions from hydrogen to full tritium and including the major D-T campaign, the nature of the various forms of collapse is investigated in all phases of the discharges. An original approach to proximity detection has been developed, which allows determining both the probability of and the time interval remaining before an incoming disruption, with adaptive, from scratch, real time compatible techniques. The results indicate that physics based prediction and control tools can be developed, to deploy realistic strategies of disruption avoidance and prevention, meeting the requirements of the next generation of devices.
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- Gurjar, Mrugaja, 1997, et al.
(författare)
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Automated data extraction tool (DET) for external applications in radiotherapy.
- 2023
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Ingår i: Technical innovations & patient support in radiation oncology. - : Elsevier BV. - 2405-6324. ; 25
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Tidskriftsartikel (refereegranskat)abstract
- Oncological Information Systems (OIS) manage information in radiotherapy (RT) departments. Due to database structure limitations, stored information can rarely be directly used except for vendor-specific purposes. Our aim is to enable the use of such data in various external applications by creating a tool for automatic data extraction, cleaning and formatting.We used OIS data from a nine-linac RT department in Sweden (70weeks, 2015-16). Extracted data included patients' referrals and appointments with details for RT sub-tasks. The data extraction tool to prepare the data for external use was built in C# programming language. It used excel-automation queries to remove unassigned/duplicated values, substitute missing data and perform application-specific calculations. Descriptive statistics were used to verify the output with the manually prepared dataset from the corresponding time period.From the initial raw data, 2030 (51%)/907 (23%) patients had known curative and palliative treatment intent for 84 different cancer diagnoses. After removal of incomplete entries, 373 (10%) patients had unknown treatment intents which were substituted based on the known curative/palliative ratio. Automatically- and manuallyprepared datasets differed<1% for Mould, Treatment planning, Quality assurance and±5% for Fractions and Magnetic resonance imaging with overestimations in 80/140 (57%) entries by the tool.We successfully implemented a software tool to prepare ready-to-use OIS datasets for external applications. Our evaluations showed overall results close to the manually-prepared dataset. The time taken to prepare the dataset using our automated strategy can reduce the time for manual preparation from weeks to seconds.
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