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At least 37 records · Page 2

The upgraded data acquisition system for beam loss monitoring at the Fermilab Tevatron and Main Injector

A VME-based data acquisition system for beam-loss monitors has been developed and is in use in the Tevatron and Main Injector accelerators at the Fermilab complex. The need for enhanced beam-loss protection when the Tevatron is operating in collider-mode was the main driving force for the new design. Prior to the implementation of the present system, the beam-loss monitor system was disabled during collider operation and protection of the Tevatron magnets relied on the quench protection system. The new Beam-Loss Monitor system allows appropriate abort logic and thresholds to be set over the full set of collider operating conditions. The system also records a history of beam-loss data prior to a beam-abort event for post-abort analysis. Installation of the Main Injector system occurred in the fall of 2006 and the Tevatron system in the summer of 2007. Both systems were fully operation by the summer of 2008. In this paper we report on the overall system design, provide a description of its normal operation, and show a number of examples of its use in both the Main Injector and Tevatron.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Analysis of beam loss induced abort kicker instability

Through more than a decade of operation, we have noticed the phenomena of beam loss induced kicker instability in the RHIC beam abort systems. In this study, we analyze the short term beam loss before abort kicker pre-fire events and operation conditions before capacitor failures. Beam loss has caused capacitor failures and elevated radiation level concentrated at failed end of capacitor has been observed. We are interested in beam loss induced radiation and heat dissipation in large oil filled capacitors and beam triggered thyratron conduction. We hope the analysis result would lead to better protection of the abort systems and improved stability of the RHIC operation.

43 PARTICLE ACCELERATORS↗

Modelling Beam Loss Within the LANSCE Proton Storage Ring

Several upgrades are being considered for the proton storage ring (PSR) at the Los Alamos Neutron Science Center (LANSCE) to reduce beam loss and thereby reduce the cooldown period of the PSR following a beam run. First, we have considered an increased beam pipe diameter would reduce beam loss due to beam scraping caused by misalignments and tuning errors. However, this would require increased pole-to-pole gap height within the dipoles and quadrupoles, which would change their effective length and alter their fringe fields. The effect of different magnet gaps on the beam optical parameters and on beam loss was studied using the simulation codes MAD-X and PyORBIT. Second, we are developing a detailed particle tracking model within the framework of the simulation package General Particle Tracer (GPT) for the PSR H - stripping system. This model will be used to study the effect of the stripper foil parameters (position, composition, areal density, depth, etc.) on first-turn losses, where most of the observed beam loss and emittance growth occurs due to foil scattering, foil stripping, and Lorentz stripping. The model implements C++ custom elements created to model foil scattering, foil stripping, and Lorentz stripping, as these are not built-in features of GPT. The preliminary results of the MAD-X and PyORBIT simulations, as well as the GPT simulation model, is described in this tech note.

43 PARTICLE ACCELERATORS↗

Beam Loss Monitors for NSLS-II Storage Ring

The shielding for the NSLS-II storage ring will provide adequate protection for the full injected beam losses in two cells of the ring around the injection point, but the remainder of the ring is shielded for lower losses of <10% top-off injection beam current. This will require a system to insure that beam losses do not exceed levels for a period of time that could cause excessive radiation exposure outside the shield walls. This beam Loss Control and Monitoring system will have beam loss monitors that will measure where the beam charge is lost around the ring, to warn operators if losses approach the design limits. To measure the charge loss quantitatively, we propose measuring the electron component of the shower as beam electrons hit the vacuum chamber (VC) wall. This will be done using the Cerenkov light as electrons transit ultra-pure fused silica rods placed close to the inner edge of the VC. The entire length of the rod will collect light from the electrons of the spread out shower resulting from the small glancing angle of the lost beam particles to the VC wall. The design and measurements results of the prototype Cerenkov BLM will be presented.

43 PARTICLE ACCELERATORS↗

Analysis of beam loss mechanism in the Project X linac

Minimization of the beam losses in a multi-MW H{sup -} linac such as ProjectX to a level below 1 W/m is a challenging task. The impact of different mechanism of beam stripping, including stripping in electric and magnetic fields, residual gas, blackbody radiation and intra-beam stripping, is analyzed. Other sources of beam losses are misalignements of beamline elements and errors in RF fields and phases. We present in this paper requirements for dynamic errors and correction schemes to keep beam losses under control.

43 PARTICLE ACCELERATORS↗

FPGA Architectures for Distributed ML Systems for Real-time Beam Loss De-blending

The Accelerator Real-time Edge AI for Distributed Systems (READS) project’s goal is to create a Artificial Intelligence (AI) system for real-time beam loss de-blending within the accelerator enclosure, which houses two accelerators: the Main Injector (MI) and the Recycler Ring (RR). In periods of joint operation, when both machines contain high intensity beam, radioactive beam losses from MI and RR overlap on the enclosure’s beam loss monitoring Beam Loss Monitor (BLM) system, making it difficult to attribute those losses to a single machine. Incorrect diagnoses result in unnecessary downtime that incurs both financialand experimental cost. The ML system will automatically disentangle each machine’s contributions to those measured losses, while not disrupting the existing operations-critical functions of the BLM system. This paper will focus on the evolution of the architectures, which provided the high-frequency, low-latency collection of synchronized data streams to make real-time inferences. The ML models, used for learning both local and global machine signatures and producing high quality inferences based on raw BLM loss measurements, will only be discussed at a high-level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

BEAM LOSS MECHANISMS IN HIGH INTENSITY LINACS

In the present operation of the Oak Ridge Spallation Neutron Source, 60-Hz, 825-us H beam pulses are accelerated to 910 MeV, and then compressed to less than a microsecond in the storage ring, to deliver 1 MW of beam power to the spallation target. The beam loss in the superconducting portion of the linac is higher than expected, and it has shown a surprising counter-intuitive correlation with quadrupole magnetic fields, with a loss minimum occurring when the quadrupoles are set to approximately half their design values. This behavior can now be explained by a recent set of experiments that show the beam loss is primarily due to intra-beam stripping. Beam halo is another important beam loss contributor, and collimation in the 2.5 MeV Medium Energy Beam Transport has proven to be an effective mitigation strategy. In this presentation, we will summarize these and other beam loss mechanisms that are important for high intensity linacs.

Plum, Michael A↗

Real-Time Edge AI for Distributed Systems (READS): Progress on Beam Loss De-Blending for the Fermilab Main Injector and Recycler

The Fermilab Main Injector enclosure houses two accelerators, the Main Injector and Recycler. During normal operation, high intensity proton beams exist simultaneously in both. The two accelerators share the same beam loss monitors (BLM) and monitoring system. Beam losses in the Main Injector enclosure are monitored for tuning the accelerators and machine protection. Losses are currently attributed to a specific machine based on timing. However, this method alone is insufficient and often inaccurate, resulting in more difficult machine tuning and unnecessary machine downtime. Machine experts can often distinguish the correct source of beam loss. This suggests a machine learning (ML) model may be producible to help de-blend losses between machines. Work is underway as part of the Fermilab Real-time Edge AI for Distributed Systems Project (READS) to develop a ML empowered system that collects streamed BLM data and additional machine readings to infer in real-time, which machine generated beam loss.

43 PARTICLE ACCELERATORS↗

Beam Loss Control for the NSLS-II Storage Ring

The shielding design for the NSLS-II storage ring is designed for the full injected beam losses in two periods of the ring around the injection point, but for the remainder of the ring its shielded for {le} 10% top-off injection beam. This will require a system to insure that beam losses do not exceed these levels for time sufficient to cause excessive radiation exposure outside the shield walls. This beam Loss Control and Monitoring (LCM) system will control the beam losses to the more heavily shielded injection region while monitoring the losses outside this region. To achieve this scrapers are installed in the injection region to intercept beam particles that might be lost outside this region. The scrapers will be thin (< 1Xrad) that will allow low energy electrons to penetrate and the subsequent dipole will separate them from the stored beam. These thin scrapers will reduce the radiation from the scraper compared to thicker scrapers. The dipole will provide significant local shielding for particles that hit inside the gap and a source for the loss monitor system that will measure the amount of beam lost in the injection region.

43 PARTICLE ACCELERATORS↗

Effect of energy interlock on possible beam losses in the Booster to Storage Ring transfer line

Under normal operational conditions in NSLS-II the energy of the beam extracted from the Booster and transferred to and injected into the Storage Ring (SR) is 3 GeV. It was determined that for the commissioning purposes energy range of the beam reaching the SR is allowed to be 2 GeV - 3.15 GeV. While the upper limit of the beam energy is defined by the maximum possible settings of Booster dipoles at the top of the ramp, the lower energy limit has to be provided by magnet interlocks. Dynamic interlocks of the Booster dipoles would be an ideal solution, yet the constraints of time and resources do not allow providing such interlocks for commissioning stage of NSLS-II. Therefore, the static interlock of two bends in the Booster to SR transfer line (BSR) will be used - the bends B1 and B2 will be interlocked within 5% of their nominal values. The possible energy of the beam reaching each BSR magnet strongly depends on the details of interlock scheme. Thus, the possible beam losses in the BSR transfer line have to be calculated taking into account the particular energy interlock. The purpose of this exercise is to determine the potential beam loss locations, for further identification of the radiation risks they impose outside the existing bulk shielding, and specification of the supplemental shielding design necessary to mitigate those risks. We will present the beam systems description along with their planned operating ranges, which forms the basis of our analysis. Next, we will find the range of beam energy that can possibly be experienced by each BSR magnet. Finally, we will describe the method used to determine potential beam loss locations and we will present the results of our studies in a form of convenient to use table which includes all the information necessary for analysis of radiation risks induced by the determined beam losses. In the following analysis we assume, unless the opposite is indicated in the clearest possible terms, that the accelerator is configured in any feasible way that its design allows.

43 PARTICLE ACCELERATORS↗

Latent diffusion can map beam loss to two-dimensional phase-space projections

Beam loss monitors (BLMs) and beam current monitors (BCMs) are ubiquitous at particle accelerators around the world. These simple devices provide noninvasive high-level beam measurements but give no insight into the detailed 6D (𝑥,𝑦,𝑧,𝑝 𝑥 ,𝑝 𝑦 ,𝑝 𝑧 ) beam phase-space distributions or dynamics. We show that generative conditional latent diffusion models can learn intricate patterns to solve the extreme inverse problem of mapping waveforms of tens of BLMs or BCMs along an accelerator to detailed 2D projections of a charged particle beam’s 6D phase-space density. This transformational method can be used at any particle accelerator to transform simple noninvasive devices into detailed beam phase-space diagnostics. We demonstrate this concept via multiparticle simulations of the high-intensity beam in the kilometer-long Los Alamos Neutron Science Center linear proton accelerator.

43 PARTICLE ACCELERATORS↗

Calibration of Fast Fiber-Optic Beam Loss Monitors for the Advanced Photon Source Storage Ring Superconducting Undulators

We report on the calibration and use of fast fiber-optic (FO) beam loss monitors (BLMs) in the Advanced Photon Source storage ring (SR). A superconducting undulator prototype (SCU0) has been operating in SR Sector 6 (“ID6”) since the beginning of CY2013, and another undulator SCU1 (a 1.1-m length undulator that is three times the length of SCU0) is scheduled for installation in Sector 1 (“ID1”) in 2015. The SCU0 main coil often quenches during beam dumps. MARS simulations have shown that relatively small beam loss (<1 nC) can lead to temperature excursions sufficient to cause quenchingwhen the SCU0windings are near critical current. To characterize local beam losses, high-purity fused-silica FO cables were installed in ID6 on the SCU0 chamber transitions and in ID1 where SCU1 will be installed. These BLMs aid in the search for operating modes that protect the SCU structures from beam-loss-induced quenching. In this paper, we describe the BLM calibration process that included deliberate beam dumps at locations of BLMs. We also compare beam dump events where SCU0 did and did not quench.

Dooling, J.↗

Electron beam loss assumptions for ELI-NPMEGa-ray radioprotection analysis

The ELI-NP project is now working on the design of their conventional facility. Dr. Gheorghe Cata-Danil recently requested that I provide them with information on the location and amount of electron-beam loss in the MEGa-ray source they have proposed for ELI-NP. This memo is intended to document that information, for transmission to ELI-NP. The ELI-NP MEGa-ray source, as presently proposed, consists of two x-band accelerator sections separated by a large chicane, as show in figure 1. The basic parameters of the machine that are pertinent for specifying the radiation source terms are shown in table 1. These are the parameters of the intentionally-produced photobeam. In addition to the photobeam, the electron gun and accelerator will produce 'dark current' that originates throughout the RF structures (that is, distributed along the accelerator axis) and therefore has a distribution of energy below the energy of the photobeam. Because it is emitted from surfaces inside the RF structures, much of it is not transported through the accelerator and is lost in the accelerator RF structures. A large fraction of the total dark current is produced in the photogun and lost at the entrance of the 1st accelerator RF structure. Important sources of radiation during operation are beam alignment screens that are used for observing the image of the electron beam, during adjustment of beam steering and for general diagnostic purposes. Each screen consists of a 1 mm thick Ce:YAG plate that is moved into the path of the beam when desired. This destroys the electron beam, spraying all beam current into the structures downstream of the screen. Only one screen is inserted at a time. These screens may be located after each accelerator RF structure, and after each set of bend magnets, as shown in figure 3. The photobeam energy and currents at each location are listed in table 2; for simplicity, the dark current energy is (conservatively) assumed to be the same as the photobeam energy. In normal operation, the locations of other beam losses and the estimated current and energy of the lost beam are listed in table 3. In addition to these 'normal' beam losses, it is assumed that the beam may be accidentally mis-steered by up to 1 degree at every steering magnet, so that it hits the surrounding beam tube and other structures. This loss can be modeled as occurring at the locations listed in table 2, numbers 1-7 and 16-21. Similarly, it is assumed that any of the dipole magnets, in chicanes or at the beam dump, may fail, resulting in total beam loss straight ahead. These locations can be assumed to be the same as listed in table 2, numbers 8-10, 12-14, 22-24, 26, and 27. The data provided above are estimates of the beam loss, for the purpose of calculating radiation source terms. Dark current estimates are conservative, until we acquire actual operational data. Neither the estimated currents nor the estimated energies listed above contain any intentional margin. when they have performed similar calculations for their own purposes, they have typically added approximately 10% to the beam energy to provide some overall margin in the analysis.

42 ENGINEERING↗

Extremum Seeking-Based Control System for Particle Accelerator Beam Loss Minimization

Particle accelerators throughout the world vary widely in terms of age and availability of advanced noninvasive diagnostics that provide varying levels of detail about the accelerated beams. Additionally, beam loss measurements and current monitors are ubiquitous in the accelerator community, they are noninvasive, and they are some of the most important metrics in terms of preventing damage or irradiation of beam pipes and equipment for high-energy machines. However, beam loss and current measurements are difficult to use for feedback tuning because of a lack of a known analytic relationship between scalar loss measurements throughout an accelerator and the hundreds of thousands of parameters that influence the beam and time variation of the beam source itself. In this work, we present a model-independent extremum seeking (ES) controller, which has been implemented for automated tuning and optimization of the Los Alamos Neutron Science Center (LANSCE) linear ion accelerator based only on scalar quantities, such as beam loss or flux measurements. We demonstrate the approach on various accelerator subsystems, including groups of radio frequency (RF) accelerating cavities, quadrupole magnets, bending magnets, and steering magnets. This tool is now available as a use graphical user interface (GUI) in the LANSCE control room, allowing beam physicists to choose arbitrary groups of parameters and beam loss or current monitors for adaptive tuning.

43 PARTICLE ACCELERATORS↗

BEAM LOSS MITIGATION IN THE OAK RIDGE SPALLATION NEUTRON SOURCE

The Oak Ridge Spallation Neutron Source (SNS) accelerator complex routinely delivers 1 MW of beam power to the spallation target. Due to this high beam power, understanding and minimizing the beam loss is an ongoing focus area of the accelerator physics program. In some areas of the accelerator facility the equipment parameters corresponding to the minimum loss are very different from the design parameters. In this presentation we will summarize the SNS beam loss measurements, the methods used to minimize the beam loss, and compare the design vs. the loss-minimized equipment parameters.

Plum, Michael A↗

Beam Losses for the PIP-III Linac to Recycler/Main Injector

The PIP-III linac produces 8 GeV H - beam for injection into the Recycler or Main Injector (MI). Beam losses throughout the system must remain low to ensure high intensity in the MI cycle and to manage radiation effects to acceptable levels, including enabling practical maintenance of the facility. Beam loss mechanisms in the system mageable maintStripping to H+ is needed, in a system that is vulnerable to magnetic stripping of H- in magnetic fields. The High power beam will heat stripping foils, perhaps unacceptably. The injection pulse is much longer than the MI circumference, so multiturn pulses with resulting heating and beam diffusion are required. We discuss beam loss related design considerations for the Linac-based scenario.

43 PARTICLE ACCELERATORS↗

Feasibility of using crystal channeling for the beam loss mitigation in Slow Extraction at 8GeV

The mitigation of the beam losses in slow extraction is becoming more and more demanding in accelerator applications for HEP as the beam power is gradually increasing. The successful demonstration of using the proton beam channeling at 450GeV to deflect the beam away from the extraction septa opens the new levels of improving the slow extraction efficiency. It is yet to be demonstrated that this method is still effective at low and medium proton beam energies. Here we present the promising results of the recent computer simulation studies of the septum shadowing at 8GeV for the Mu2e project slow extraction at Fermilab. Depending on the beam parameters the beam loss reduction is shown to be achievable in the range of 1/3 to factor of 3.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Semantic Regression for Disentangling Beam Losses in the Fermilab Main Injector and Recycler

Fermilab’s Main Injector enclosure houses two accelerators: the Main Injector (MI) and the Recycler (RR). In periods of joint operation, when both machines contain high intensity beam, radiative beam losses from MI and RR overlap on the enclosure’s beam loss monitoring (BLM) system, making it difficult to attribute those losses to a single machine. Incorrect diagnoses result in unnecessary downtime that incurs both financial and experimental cost. In this work, we introduce a novel neural approach for automatically disentangling each machine’s contributions to those measured losses. Using a continuous adaptation of the popular UNet architecture in conjunction with a novel data augmentation scheme, our model accurately infers the machine of origin on a per-BLM basis in periods of joint and independent operation. Crucially, by extracting beam loss information at varying receptive fields, the method is capable of learning both local and global machine signatures and producing high quality inferences using only raw BLM loss measurements.

43 PARTICLE ACCELERATORS↗