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Title: Parallel general purpose multiobjective optimization framework with application to electron beam dynamics

Abstract

Particle accelerators are invaluable tools for research in the basic and applied sciences, such as materials science, chemistry, the biosciences, particle physics, nuclear physics and medicine. The design, commissioning, and operation of accelerator facilities is a nontrivial task, due to the large number of control parameters and the complex interplay of several conflicting design goals. The Argonne Wakefield Accelerator facility has some unique challenges resulting from its purpose to carry out advanced accelerator R&D. Individual experiments often have challenging beam requirements, and the physical configuration of the beam lines is often changed to accommodate the variety of supported experiments. The need for rapid deployment of different operational settings further complicates the optimization work that must be done for multiple constraints and challenging operational regimes. One example of this is an independently staged two-beam acceleration experiment which requires the construction of an additional beam line (this is now in progress). The high charge drive beam, well into the space charge regime, must be threaded through small aperture (17.6 mm) decelerating structures. In addition, the bunch length must be sufficiently short to maximize power generation in the decelerator. We propose to tackle this problem by means of multiobjective optimization algorithms which alsomore » facilitate a parallel deployment. In order to compute solutions in a meaningful time frame, a fast and scalable software framework is required. In this paper, we present a general-purpose framework for simulation-based multiobjective optimization methods that allows the automatic investigation of optimal sets of machine parameters. Using evolutionary algorithms as the optimizer and opal as the forward solver, validation experiments and results of multiobjective optimization problems in the domain of beam dynamics are presented. Optimized solutions for the new high charge drive beam line found by the framework were used to finish the design of a two beam acceleration experiment. The selected solution along with the associated beam parameters is presented.« less

Authors:
; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
Illinois Institute of Technology, Chicago, IL (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1512835
Alternate Identifier(s):
OSTI ID: 1612292
Grant/Contract Number:  
AC02-06CH11357; SC0015479
Resource Type:
Published Article
Journal Name:
Physical Review Accelerators and Beams
Additional Journal Information:
Journal Name: Physical Review Accelerators and Beams Journal Volume: 22 Journal Issue: 5; Journal ID: ISSN 2469-9888
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; 43 PARTICLE ACCELERATORS; Physics

Citation Formats

Neveu, N., Spentzouris, L., Adelmann, A., Ineichen, Y., Kolano, A., Metzger-Kraus, C., Bekas, C., Curioni, A., and Arbenz, P.. Parallel general purpose multiobjective optimization framework with application to electron beam dynamics. United States: N. p., 2019. Web. https://doi.org/10.1103/PhysRevAccelBeams.22.054602.
Neveu, N., Spentzouris, L., Adelmann, A., Ineichen, Y., Kolano, A., Metzger-Kraus, C., Bekas, C., Curioni, A., & Arbenz, P.. Parallel general purpose multiobjective optimization framework with application to electron beam dynamics. United States. https://doi.org/10.1103/PhysRevAccelBeams.22.054602
Neveu, N., Spentzouris, L., Adelmann, A., Ineichen, Y., Kolano, A., Metzger-Kraus, C., Bekas, C., Curioni, A., and Arbenz, P.. Wed . "Parallel general purpose multiobjective optimization framework with application to electron beam dynamics". United States. https://doi.org/10.1103/PhysRevAccelBeams.22.054602.
@article{osti_1512835,
title = {Parallel general purpose multiobjective optimization framework with application to electron beam dynamics},
author = {Neveu, N. and Spentzouris, L. and Adelmann, A. and Ineichen, Y. and Kolano, A. and Metzger-Kraus, C. and Bekas, C. and Curioni, A. and Arbenz, P.},
abstractNote = {Particle accelerators are invaluable tools for research in the basic and applied sciences, such as materials science, chemistry, the biosciences, particle physics, nuclear physics and medicine. The design, commissioning, and operation of accelerator facilities is a nontrivial task, due to the large number of control parameters and the complex interplay of several conflicting design goals. The Argonne Wakefield Accelerator facility has some unique challenges resulting from its purpose to carry out advanced accelerator R&D. Individual experiments often have challenging beam requirements, and the physical configuration of the beam lines is often changed to accommodate the variety of supported experiments. The need for rapid deployment of different operational settings further complicates the optimization work that must be done for multiple constraints and challenging operational regimes. One example of this is an independently staged two-beam acceleration experiment which requires the construction of an additional beam line (this is now in progress). The high charge drive beam, well into the space charge regime, must be threaded through small aperture (17.6 mm) decelerating structures. In addition, the bunch length must be sufficiently short to maximize power generation in the decelerator. We propose to tackle this problem by means of multiobjective optimization algorithms which also facilitate a parallel deployment. In order to compute solutions in a meaningful time frame, a fast and scalable software framework is required. In this paper, we present a general-purpose framework for simulation-based multiobjective optimization methods that allows the automatic investigation of optimal sets of machine parameters. Using evolutionary algorithms as the optimizer and opal as the forward solver, validation experiments and results of multiobjective optimization problems in the domain of beam dynamics are presented. Optimized solutions for the new high charge drive beam line found by the framework were used to finish the design of a two beam acceleration experiment. The selected solution along with the associated beam parameters is presented.},
doi = {10.1103/PhysRevAccelBeams.22.054602},
journal = {Physical Review Accelerators and Beams},
number = 5,
volume = 22,
place = {United States},
year = {2019},
month = {5}
}

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    Constrained multiobjective shape optimization of superconducting rf cavities considering robustness against geometric perturbations
    journal, December 2019