Mauro Giacchini (Istituto Nazionale di Fisica Nucleare)
SUSB012
Advanced algorithms for linear accelerator design and operation
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In this paper, we investigate the usage of advanced algorithms adapted for optimizing the design and operation of different linear accelerators (LINACs), notably the superconducting linac ALPI at INFN-LNL and the ANTHEM BNCT facility to be constructed at Caserta, Italy. Utilizing various intelligent algorithms and machine learning techniques such as Bayesian optimization, genetic algorithms, particle swarm optimization, and surrogate modeling with artificial neural networks, we aim to enhance the design efficiency, operational reliability and adaptability of linear accelerators. Through simulations and case studies, we demonstrate the effectiveness and practical implications of these algorithms for optimizing LINAC performances across diverse applications.
DOI: reference for this paper: 10.18429/JACoW-LINAC2024-TUPB075
About: Received: 14 Aug 2024 — Revised: 27 Aug 2024 — Accepted: 28 Aug 2024 — Issue date: 23 Oct 2024
Construction status of the IFMIF-DONES 5 MW linac
IFMIF-DONES (International Fusion Materials Irradiation Facility - DEMO-Oriented NEutron Source) is a facility under construction as part of the European fusion roadmap. The facility, located in Granada (Spain), is a powerful neutron irradiation facility for validation and qualification of materials to be used in fusion reactors. The construction of the facility under the framework of the DONES Programme started in March 2023, following the first DONES Steering Committee. Currently, the design is being transferred to the DONES Programme, and the first bunch of in-kind contributions are being agreed, including the ones for the construction of the 5 MW deuteron superconducting linear accelerator. The design has been consolidated during the last years through the LIPAc (Linear IFMIF Prototype Accelerator), but also to other prototypes of critical parts of the accelerator among different frameworks. These include high-power solid-state amplifiers, superconducting cavities and beam diagnostics. Most of them are already validated, while a few are still undergoing validation. In this contribution, the status of the design and manufacturing of the 5 MW linear accelerator will be reviewed, including the prototypes and validation activities being carried out under several projects.
TUPB075
Advanced algorithms for linear accelerator design and operation
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In this paper, we investigate the usage of advanced algorithms adapted for optimizing the design and operation of different linear accelerators (LINACs), notably the superconducting linac ALPI at INFN-LNL and the ANTHEM BNCT facility to be constructed at Caserta, Italy. Utilizing various intelligent algorithms and machine learning techniques such as Bayesian optimization, genetic algorithms, particle swarm optimization, and surrogate modeling with artificial neural networks, we aim to enhance the design efficiency, operational reliability and adaptability of linear accelerators. Through simulations and case studies, we demonstrate the effectiveness and practical implications of these algorithms for optimizing LINAC performances across diverse applications.
Paper: TUPB075
DOI: reference for this paper: 10.18429/JACoW-LINAC2024-TUPB075
About: Received: 14 Aug 2024 — Revised: 27 Aug 2024 — Accepted: 28 Aug 2024 — Issue date: 23 Oct 2024