IPAC2021 - List of Authors (Milas, N.)

Paper	Title	Page
TUPAB176	ESS Proton Beam Trajectory Correction	1809
	N. Blaskovic Kraljevic, M. Eshraqi, N. Milas, R. Miyamoto ESS, Lund, Sweden
	The proton linac of the European Spallation Source (ESS) is under construction in Lund, Sweden. Beam trajectory correction is essential to mitigate the effect of accelerator element misalignment, constituting the first step to minimise beam losses. The correction will be performed using correctors distributed along the accelerator, based on the beam position monitor (BPM) readout. Three trajectory correction techniques are considered: one-to-one steering, Singular Value Decomposition (SVD), and MICADO (selecting a subset of correctors for the trajectory correction). The performance of the three methods is simulated for the ESS linac and a comparison of the outcomes is presented.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB176
About •	paper received ※ 19 May 2021 paper accepted ※ 15 June 2021 issue date ※ 27 August 2021
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPAB198	ESS DTL Tuning Using Machine Learning Methods	1872
	J.S. Lundquist, N. Milas, E. Nilsson ESS, Lund, Sweden S. Werin Lund University, Lund, Sweden
	The European Spallation Source, currently under construction in Lund, Sweden, will be the world’s most powerful neutron source. It is driven by a proton linac with a current of 62.5 mA, 2.86 ms long pulses at 14 Hz. The final section of its normal-conducting front-end consists of a 39 m long drift tube linac (DTL) divided into five tanks, designed to accelerate the proton beam from 3.6 MeV to 90 MeV. The high beam current and power impose challenges to the design and tuning of the machine and the RF amplitude and phase have to be set within 1% and 1 degree of the design values. The usual method used to define the RF set-point is signature matching, which can be a time consuming and challenging process, and new techniques to meet the growing complexity of accelerator facilities are highly desirable. In this paper we study the usage of Machine Learning to determine the RF optimum amplitude and phase. The data from a simulated phase scan is fed into an artificial neural network in order to identify the needed changes to achieve the best tuning. Our test for the ESS DTL1 shows promising results, and further development of the method will be outlined.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB198
About •	paper received ※ 17 May 2021 paper accepted ※ 21 June 2021 issue date ※ 13 August 2021
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPAB319	Open XAL Status Report 2021	3421
	N. Milas, J.F. Esteban Müller, E. Laface, Y. Levinsen ESS, Lund, Sweden T.V. Gorlov, A.P. Shishlo, A.P. Zhukov ORNL, Oak Ridge, Tennessee, USA
	The Open XAL accelerator physics software platform is being developed through international collaboration among several facilities since 2010. The goal of the collaboration is to establish Open XAL as a multi-purpose software platform supporting a broad range of tool and application development in accelerator physics and high-level control (Open XAL also ships with a suite of general-purpose accelerator applications). This paper discusses progress in beam dynamics simulation, new RF models, and updated application framework along with new generic accelerator physics applications. We present the current status of the project, a roadmap for continued development, and an overview of the project status at each participating facility.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEPAB319
About •	paper received ※ 19 May 2021 paper accepted ※ 21 July 2021 issue date ※ 11 August 2021
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

ESS Proton Beam Trajectory Correction

1809

N. Blaskovic Kraljevic, M. Eshraqi, N. Milas, R. Miyamoto
ESS, Lund, Sweden

The proton linac of the European Spallation Source (ESS) is under construction in Lund, Sweden. Beam trajectory correction is essential to mitigate the effect of accelerator element misalignment, constituting the first step to minimise beam losses. The correction will be performed using correctors distributed along the accelerator, based on the beam position monitor (BPM) readout. Three trajectory correction techniques are considered: one-to-one steering, Singular Value Decomposition (SVD), and MICADO (selecting a subset of correctors for the trajectory correction). The performance of the three methods is simulated for the ESS linac and a comparison of the outcomes is presented.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB176

About •

paper received ※ 19 May 2021 paper accepted ※ 15 June 2021 issue date ※ 27 August 2021

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPAB198

ESS DTL Tuning Using Machine Learning Methods

1872

J.S. Lundquist, N. Milas, E. Nilsson
ESS, Lund, Sweden
S. Werin
Lund University, Lund, Sweden

The European Spallation Source, currently under construction in Lund, Sweden, will be the world’s most powerful neutron source. It is driven by a proton linac with a current of 62.5 mA, 2.86 ms long pulses at 14 Hz. The final section of its normal-conducting front-end consists of a 39 m long drift tube linac (DTL) divided into five tanks, designed to accelerate the proton beam from 3.6 MeV to 90 MeV. The high beam current and power impose challenges to the design and tuning of the machine and the RF amplitude and phase have to be set within 1% and 1 degree of the design values. The usual method used to define the RF set-point is signature matching, which can be a time consuming and challenging process, and new techniques to meet the growing complexity of accelerator facilities are highly desirable. In this paper we study the usage of Machine Learning to determine the RF optimum amplitude and phase. The data from a simulated phase scan is fed into an artificial neural network in order to identify the needed changes to achieve the best tuning. Our test for the ESS DTL1 shows promising results, and further development of the method will be outlined.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB198

About •

paper received ※ 17 May 2021 paper accepted ※ 21 June 2021 issue date ※ 13 August 2021

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPAB319

Open XAL Status Report 2021

3421

N. Milas, J.F. Esteban Müller, E. Laface, Y. Levinsen
ESS, Lund, Sweden
T.V. Gorlov, A.P. Shishlo, A.P. Zhukov
ORNL, Oak Ridge, Tennessee, USA

The Open XAL accelerator physics software platform is being developed through international collaboration among several facilities since 2010. The goal of the collaboration is to establish Open XAL as a multi-purpose software platform supporting a broad range of tool and application development in accelerator physics and high-level control (Open XAL also ships with a suite of general-purpose accelerator applications). This paper discusses progress in beam dynamics simulation, new RF models, and updated application framework along with new generic accelerator physics applications. We present the current status of the project, a roadmap for continued development, and an overview of the project status at each participating facility.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEPAB319

About •

paper received ※ 19 May 2021 paper accepted ※ 21 July 2021 issue date ※ 11 August 2021

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)