NAPAC2019 - List of Authors (Venturini, M.)

Paper	Title	Page
MOZBA6	The Broad-Band Impedance Budget of the Accumulator Ring in the ALS-U Project	74
MOPLM26	use link to see paper's listing under its alternate paper code
	D. Wang, S. De Santis, D. Li, T.H. Luo, M. Venturini LBNL, Berkeley, California, USA K.L.F. Bane SLAC, Menlo Park, California, USA
	Design work is underway for the upgrade of the Advanced Light Source (ALS-U) to a diffraction-limited soft x-rays radiation source. It consists of an accumulator and a storage ring. In both rings, coupling-impedance driven instabilities need careful evaluation to ensure meeting the machine high-performance goals. This paper presents the impedance budget of the accumulator ring both longitudinally and transversely. The budget includes the resistive wall impedance as well as the geometric impedance from the main vacuum components. Our calculations primarily rely on electromagnetic simulations with the CST code; when possible validation has been sought against analytical modeling, typically in the low-frequency limit, and good agreement generally found. Collective-instability current thresholds are also discussed.
	Slides MOZBA6 [8.926 MB]
	Poster MOZBA6 [3.542 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-NAPAC2019-MOZBA6
About •	paper received ※ 27 August 2019 paper accepted ※ 06 September 2019 issue date ※ 08 October 2019
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPLM04	First Attempts at Applying Machine Learning to ALS Storage Ring Stabilization	98
	S.C. Leemann, Ph. Amstutz, W.E. Byrne, M.P. Ehrlichman, T. Hellert, A. Hexemer, S. Liu, M. Marcus, C.N. Melton, H. Nishimura, G. Penn, F. Sannibale, D.A. Shapiro, C. Sun, D. Ushizima, M. Venturini LBNL, Berkeley, California, USA
	Funding: This research is funded by the US Department of Energy (BES & ASCR Programs), and supported by the Director of the Office of Science of the US Department of Energy under Contract No. DEAC02-05CH11231. The ALS storage ring operates multiple feedbacks and feed-forwards during user operations to ensure that various source properties such as beam position, beam angle, and beam size are maintained constant. Without these active corrections, strong perturbations of the electron beam would result from constantly varying ID gaps and phases. An important part of the ID gap/phase compensation requires recording feed-forward tables. While recording such tables takes a lot of time during dedicated machine shifts, the resulting compensation data is imperfect due to machine drift both during and after recording of the table. Since it is impractical to repeat recording feed-forward tables on a more frequent basis, we have decided to employ Machine Learning techniques to improve ID compensation in order to stabilize electron beam properties at the source points.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-NAPAC2019-MOPLM04
About •	paper received ※ 26 August 2019 paper accepted ※ 31 August 2019 issue date ※ 08 October 2019
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

MOZBA6

The Broad-Band Impedance Budget of the Accumulator Ring in the ALS-U Project

74

MOPLM26

use link to see paper's listing under its alternate paper code

D. Wang, S. De Santis, D. Li, T.H. Luo, M. Venturini
LBNL, Berkeley, California, USA
K.L.F. Bane
SLAC, Menlo Park, California, USA

Design work is underway for the upgrade of the Advanced Light Source (ALS-U) to a diffraction-limited soft x-rays radiation source. It consists of an accumulator and a storage ring. In both rings, coupling-impedance driven instabilities need careful evaluation to ensure meeting the machine high-performance goals. This paper presents the impedance budget of the accumulator ring both longitudinally and transversely. The budget includes the resistive wall impedance as well as the geometric impedance from the main vacuum components. Our calculations primarily rely on electromagnetic simulations with the CST code; when possible validation has been sought against analytical modeling, typically in the low-frequency limit, and good agreement generally found. Collective-instability current thresholds are also discussed.

Slides MOZBA6 [8.926 MB]

Poster MOZBA6 [3.542 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-NAPAC2019-MOZBA6

About •

paper received ※ 27 August 2019 paper accepted ※ 06 September 2019 issue date ※ 08 October 2019

Export •

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

MOPLM04

First Attempts at Applying Machine Learning to ALS Storage Ring Stabilization

98

S.C. Leemann, Ph. Amstutz, W.E. Byrne, M.P. Ehrlichman, T. Hellert, A. Hexemer, S. Liu, M. Marcus, C.N. Melton, H. Nishimura, G. Penn, F. Sannibale, D.A. Shapiro, C. Sun, D. Ushizima, M. Venturini
LBNL, Berkeley, California, USA

Funding: This research is funded by the US Department of Energy (BES & ASCR Programs), and supported by the Director of the Office of Science of the US Department of Energy under Contract No. DEAC02-05CH11231.
The ALS storage ring operates multiple feedbacks and feed-forwards during user operations to ensure that various source properties such as beam position, beam angle, and beam size are maintained constant. Without these active corrections, strong perturbations of the electron beam would result from constantly varying ID gaps and phases. An important part of the ID gap/phase compensation requires recording feed-forward tables. While recording such tables takes a lot of time during dedicated machine shifts, the resulting compensation data is imperfect due to machine drift both during and after recording of the table. Since it is impractical to repeat recording feed-forward tables on a more frequent basis, we have decided to employ Machine Learning techniques to improve ID compensation in order to stabilize electron beam properties at the source points.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-NAPAC2019-MOPLM04

About •

paper received ※ 26 August 2019 paper accepted ※ 31 August 2019 issue date ※ 08 October 2019

Export •

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