CERN Accelerating science

CERN Document Server 24 records found  1 - 10nextend  jump to record: Search took 0.65 seconds. 
1.
MuCol Milestone Report No. 5: Preliminary Parameters / MuCoL Collaboration
This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. [...]
arXiv:2411.02966.
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Fermilab Library Server - Fulltext - Fulltext
2.
Transient finite-element simulations of fast-ramping muon-collider magnets / Moll, Dominik (Darmstadt, Tech. U.) ; Boattini, Fulvio (CERN) ; De Gersem, Herbert (Darmstadt, Tech. U.) ; Christmann, Jan-Magnus (Darmstadt, Tech. U.) ; D'Angelo, Laura (Darmstadt, Tech. U.) ; Bottura, Luca (CERN) ; Breschi, Marco (Bologna U.)
Conceptual studies for a muon collider identify fast-ramping magnets as a major design challenge. Rise rates of more than 1 T/ms are attainable with normal-conducting magnets, incorporating iron yokes to make sure that stored magnetic energies and inductances stay below reasonable thresholds. [...]
2024 - 4 p. - Published in : JACoW IPAC 2024 (2024) TUPR54 Fulltext: PDF;
In : 15th International Particle Accelerator Conference (IPAC 2024), Nashville, TN, United States, 19 - 24 May 2024, pp.TUPR54
3.
Cover not available Interim report for the International Muon Collider Collaboration / Accettura, C.
The International Muon Collider Collaboration (IMCC) [1] was established in 2020 following the recommendations of the European Strategy for Particle Physics (ESPP) and the implementation of the European Strategy for Particle Physics-Accelerator R&D Roadmap by the Laboratory Directors Group [2], [...]
arXiv:2407.12450 ; CERN-2024-002 - Geneva : CERN, 2024-09-30 - 150. (CERN Yellow Reports: Monographs ; 2/2024)


e-book
4.
Investigation of the nucleon distribution on the surface of radioactive xenon nuclei using antiprotons / Aberle, Oliver (CERN, 1211 Geneva 23, Switzerland) ; Aumann, Tom (Institut für Kernphysik, Technische Universität Darmstadt, 64289 Darmstadt, Germany) ; Azaryan, Nikolay (CERN, 1211 Geneva 23, Switzerland) ; Bissell, Mark Lloyd (CERN, 1211 Geneva 23, Switzerland) ; Boine-Frankenheim, Oliver (Institut für Teilchenbeschleunigung und elektromagnetische Felder, Technische Universität Darmstadt, 64289 Darmstadt, Germany) ; Bonnes, Uwe (Institut für Kernphysik, Technische Universität Darmstadt, 64289 Darmstadt, Germany) ; Butin, Francois (CERN, 1211 Geneva 23, Switzerland) ; Chiggiato, Paolo (CERN, 1211 Geneva 23, Switzerland) ; De Gersem, Herbert (Institut für Teilchenbeschleunigung und elektromagnetische Felder, Technische Universität Darmstadt, 64289 Darmstadt, Germany) ; De Oliveira, Rui (CERN, 1211 Geneva 23, Switzerland) et al.
CERN-INTC-2024-055 ; INTC-P-712.
- 2024
Full text
5.
Not yet available
Modelling and simulating accelerator magnets / De Gersem, Herbert (speaker)
In this lecture, we show how to set up a finite element model of an accelerator magnet. We discuss the challenges in simulating accelerator magnets and come up with a list of requirements for commercial or freeware simulation tools. [...]
2023 - 3315. CERN Accelerator School; CAS course on "Normal- and Superconducting Magnets", 19 November - 02 December 2023, St. Pölten, Austria External links: Talk details; Event details In : CAS course on "Normal- and Superconducting Magnets", 19 November - 02 December 2023, St. Pölten, Austria
6.
Not yet available
Magnetic field simulation by finite element methods / De Gersem, Herbert (speaker)
Stephan Russenschuck, Maxwell equations in global form, oriented manifolds, Ampere’s law, Faraday’s law, Gauss’ law, conservation of charge. Maxwell equation in local form, Vector fields, application to NC magnets, material relations, boundary and interface conditions, space curves and their applications, CCT magnets, the directional derivative, grad, curl, and div, coordinate-free definition of the differential operators, Maxwell’s house [...]
2023 - 3468. CERN Accelerator School; CAS course on "Normal- and Superconducting Magnets", 19 November - 02 December 2023, St. Pölten, Austria External links: Talk details; Event details In : CAS course on "Normal- and Superconducting Magnets", 19 November - 02 December 2023, St. Pölten, Austria
7.
Magnets for a Muon Collider—Needs and Plans / Bottura, L (CERN) ; Accettura, C (CERN) ; Amemiya, N (Kyoto U.) ; Auchmann, B (PSI, Villigen) ; Berg, J S (Brookhaven Natl. Lab.) ; Bersani, A (INFN, Genoa) ; Bertarelli, A (CERN) ; Boattini, F (CERN) ; Bordini, B (CERN) ; Borges de Sousa, P (CERN) et al.
We describe the magnet challenges for a Muon Collider, an exciting option considered for the future of particle physics at the energy frontier. Starting from the comprehensive work performed by the US Muon Accelerator Program, we have reviewed the performance specifications dictated by beam physics and the operating conditions to satisfy the accelerator needs. [...]
2024 - 8 p. - Published in : IEEE Trans. Appl. Supercond. 34 (2024) 1-8 Fulltext: PDF;
8.
Efficient Reduced Magnetic Vector Potential Formulation for the Magnetic Field Simulation of Accelerator Magnets / D'Angelo, Laura A.M. (Darmstadt, Tech. U.) ; Moll, Dominik (Darmstadt, Tech. U.) ; Vitrano, Andrea (CERN) ; Marsic, Nicolas (Darmstadt, Tech. U.) ; Schnaubelt, Erik (Darmstadt, Tech. U. ; CERN) ; Wozniak, Mariusz (CERN) ; De Gersem, Herbert (Darmstadt, Tech. U.) ; Auchmann, Bernhard (PSI, Villigen)
The major advantage of reduced magnetic vector potential formulations (RMVPs) is that complicated coil structures do not need to be resolved by a computational mesh. Instead, they are modeled by thin wires, whose source field is included into the simulation model along Biot-Savart's law. [...]
arXiv:2309.02004.- 2024-03 - 8 p. - Published in : IEEE Trans. Magn. 60 (2024) 7000808 Fulltext: PDF;
9.
Hybrid modeling: towards the next level of scientific computing in engineering / Kurz, Stefan ; De Gersem, Herbert (Darmstadt, Tech. Hochsch.) ; Galetzka, Armin (Darmstadt, Tech. Hochsch.) ; Klaedtke, Andreas ; Liebsch, Melvin (CERN) ; Loukrezis, Dimitrios (Darmstadt, Tech. Hochsch.) ; Russenschuck, Stephan (CERN) ; Schmidt, Manuel
AbstractThe integration of machine learning (Keplerian paradigm) and more general artificial intelligence technologies with physical modeling based on first principles (Newtonian paradigm) will impact scientific computing in engineering in fundamental ways. Such hybrid models combine first principle-based models with data-based models into a joint architecture. [...]
2022 - 12 p. - Published in : J. Math. Industry 12 (2022) 8 Fulltext: PDF;
10.
PUMA, antiProton unstable matter annihilation / PUMA Collaboration
PUMA, antiProton Unstable Matter Annihilation, is a nuclear-physics experiment at CERN aiming at probing the surface properties of stable and rare isotopes by use of low-energy antiprotons. Low-energy antiprotons offer a very unique sensitivity to the neutron and proton densities at the annihilation site, i.e. [...]
2022 - 69 p. - Published in : Eur. Phys. J. A 58 (2022) 88 Fulltext: PDF;

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