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This presentation provides an overview of organic scintillators, discusses what is DRIFT and recent developments in DRIFT, and concludes with future prospects and plans.
Helium-3 tubes are an efficient way to detect neutrons after they have thermalized by polyethylene. They are often arranged in rings to perform coincidence counting. Applications include nuclear safeguards, treaty verification, and emergency response. DRiFT has the ability to simulate pile-up, room return, and end effects. A new feature determines real and accidental correlated counts. The next steps include DRiFT 2.0 released as executable, continued demonstration of gas module capabilities, and semiconductor module under a development.
The Mu2e experiment searches for charged lepton flavor violation through muon-to-electron conversion in the field of a nucleus. The signal is a monoenergetic electron with an energy of 104.97 MeV. Its momentum is reconstructed using information from drifting ionized particles in a straw tracker detector. This project analyzes the drift of ionized particles with a deep neural network to help improve the momentum reconstruction process. The model yields a 20% improvement in resolution from a reference linear model.
High accuracy measurement systems can drift with time. Implementing a drift-eliminating design reduces measurement uncertainty and improves quality control.
The closed-off structure of the Fermilab Drift Tube Linac precludes a robust array of instrumentation from directly monitoring the H- beam that is accelerated from 750 keV to 116 MeV. To improve beam tuning and op-erational assessment of Drift Tube Linac performance, scintillator-based loss monitors were previously installed along the exterior of the first two accelerating cavities to assess low energy beam losses. Here we present a recent upgrade to the loss monitor system, including significant improvements in analog signal processing to address baseline-interfering noise; digitization of the signals to enable regular operational use and tuning; and a new remote operation upgrade of the translating loss monitor with precise positioning of the loss monitor along its nine-foot track. Data from the fixed and translating de-tectors collected under varying beam conditions validate the utility of the upgrade.
The Far Detector of the Deep Underground Neutrino Experiment (DUNE) will be a large LArdetector located at a baseline of 1300 kilometers, 1.5 km deep underground. It is planned to bemade up of four modules, each with a total mass of 17 kt of LAr, at least the first two of which willconsist in Liquid Argon Time Projection Chambers (LArTPCs). To prove the feasibility of theLArTPC technology at the kiloton scale, the ProtoDUNE Single and Dual-Phase detectors wereconstructed and operated at the CERN Neutrino facility.This document describes the Vertical Drift detector concept, which is proposed to instrument thesecond DUNE module. It consists of a TPC where the electrons drift vertically, with a cathodesuspended at mid-height, towards anodes placed at the bottom and top of the detector. The anodeswould be made out of printed PCBs instead of wires, and the new disposition would allow the topreadout electronics to be accessible during the lifetime of the experiment. An enhanced photo-detection system is also proposed, with the photo-sensors placed on the cryostat walls and thecathode, but posing a challenge in terms of power and signal transmission. Studies are ongoingboth to overcome the technical challenges of this new design and to finalize the concept.
The Fermilab Linac is a roughly 145 meter linear accelerator that accelerates H- beam from 750 keV to 400 MeV and provides beam for the Booster and the rest of the accelerator chain. The first section of the Linac is a Drift-Tube Linac (DTL), which in its current state, suffers from a lack of instrumentation along its length. As a result, operational staff do not have access to the diagnostic information needed to tune the critical components of this accelerator, such as the quadrupole magnets within the drift tubes. This work presents an effort to utilize both fixed and translating scintillation detectors to investigate beam loss along the first two cavities of the DTL.
The Mu2e experiment searches for charged lepton flavor violation through muon-to-electron conversion in the field of a nucleus. The signal is a monoenergetic electron with an energy of 104.97 MeV. Its momentum is reconstructed using information from drifting ionized particles in a straw tracker detector. This project analyzes the drift of ionized particles with a deep neural network to help improve the momentum reconstruction process. The model yields a 20% improvement in resolution from a reference linear model.
Marine energy converters can generate electricity from energetic ocean waves and water currents. Because sound is extensively used by marine animals, the radiated noise from these systems is of regulatory interest. However, the energetic nature of these locations poses challenges for performing accurate passive acoustic measurements, particularly with stationary platforms. The Drifting Acoustic Instrumentation SYstem (DAISY) is a modular hydrophone recording system purpose-built for marine energy environments. Using a flow shield in currents and mass–spring–damper suspension system in waves, we demonstrate that DAISYs can effectively minimize the masking effect of flow noise at frequencies down to 10 Hz. In addition, we show that groups of DAISYs can utilize time-delay-of-arrival post-processing to attribute radiated noise to a specific source. Consequently, DAISYs can rapidly measure radiated noise at all frequencies of interest for prototype marine energy converters. Furthermore, the resulting information from future operational deployments should support regulatory decision-making and allow technology developers to make design adjustments that minimize the potential for acoustic impacts as their systems are scaled up for utility-scale power generation.
Modern Nuclear Physics experimental setups run experiments with higher beam intensity resulting in increased noise in detector components used for particle track reconstruction. Increased uncorrelated signals (noise) result in decreased particle reconstruction efficiency. In this paper, we investigate the usage of Machine Learning, specifically Convolutional Neural Network Auto-Encoders (CAE), for de-noising raw hits from drift chambers in the CLAS12 detector. To the best of our knowledge, this is the first time CAE is employed to perform such an operation in this field. During the de-noising phase, it is important to remove as much noise as possible while retaining the valid hits to avoid losing crucial information about the experiment. Here, we show that using CAE, it is possible to remove noise hits while retaining up to 94% of valid tracks for a beam current of 110nA while for lower beam currents (45-55nA), we get up to 98% efficiency. Studies on experimental conditions with increasing noise show that CAE performs better than conventional tracking algorithms in isolating hits belonging to tracks. Specifically, the de-noising algorithm results in tracking efficiency improvements greater than 15%, in real data production procedures with nominal conditions, and up to two times better efficiency in synthetically generated data with high luminosity conditions (90-110nA), indicating that machine learning can lead to significantly shorter times for conducting physics experiments.
The CEBAF Large Acceptance Spectrometer at 12~GeV (CLAS12) is located in Hall~B, one of the experimental halls at Jefferson Lab. The forward part of CLAS12 is built around a superconducting toroidal magnet. The six coils of the toroid divide the detector azimuthally into six sectors. Each sector contains three multi-layer drift chambers for reconstructing the trajectories of charged particles originating from a fixed target. Each of the 18 planar chambers has two ``superlayers'' of six layers each, with the wires in the two adjacent superlayers oriented at ± 6° stereo angles. Each layer has 112 hexagonal cells spanning a range from about 5° to 40° in polar angle. The six-layer structure provides redundancy in track segment finding and good tracking efficiency even in the presence of some individual wire inefficiency. The design, construction, operation, and calibration methods are described, and estimates of the efficiency and resolution are presented from in-beam measurements.
Drift-wave turbulence produces anomalous transport via cross-correlations between fluctuations. This transport has profound implications for confinement, structure formation, and virtually all aspects of the non-linear turbulent dynamics. Herein, we use a data-driven method based on deep learning in order to study turbulent transport in the 2D Hasegawa–Wakatani system and infer a reduced mean-field model from numerical solution. In addition to the usual turbulent diffusion, we find an effect which couples the particle flux to the local gradient of vorticity, which tends to modulate the density profile. The direct coupling to the shear is relatively weak. In addition, the deep learning method finds a model for spontaneous zonal flow generation by negative viscosity, stabilized by non-linear and hyperviscous terms. We compare these results to analytic calculations using quasilinear theory and wave kinetics, finding qualitative agreement, though the calculations miss certain higher-order effects. A simplified, 1-D model for the evolution of the profile, flow, and intensity based on the deep learning results is solved numerically and compared to previous models for staircasing based on bistability. We see that the physics uncovered by the deep learning method provided simple explanations for the formation of zonal structures in the density, flow, and turbulence fields. We highlight the important role of symmetry in the deep learning method and speculate on the portability of the method to other applications.
A unified theory of zonal flow shears and density corrugations in drift wave turbulence is presented. Polarization and density advection beat excitation are studied in combination with modulational response. Noise is driven by two-time flux correlation. While the effective zonal flow eddy viscosity can go negative, the zonal diffusivity is positive definite. There is no inverse cascade of density corrugation. The connection between avalanches and corrugations is discussed. Here, the zonal cross-correlation is identified and calculated. Conditions for alignment of zonal shears and corrugation gradients are determined, and the implications for staircase structure are discussed. We show that the synergy of beat noise and modulational effects is stronger than either alone. Strong zonal flows can be excited well below the modulational instability threshold. In the context of L–H transition, zonal noise quenches turbulence overshoot by eliminating the threshold for zonal flow excitation. The power threshold for L–H transition is lowered.
A series of BOUT++ turbulence simulations are performed for two Pre-Fusion Power Operation (PFPO-1,2) phases of the ITER Research plan proclaimed in 2019. Linear simulation results show that PFPO-1 is unstable to Peeling-ballooning modes (PB), while the PFPO-2 is unstable to the coupling of PB and Drift-Alfvén wave (DAW) instabilities. The linear results are qualitatively consistent with the dispersion relation of DAW. To study the influence of the DAW on the edge-localized mode (ELM) crash, the PFPO-2 is adopted in this section. Different from the grassy ELM in [Li et al 2022 Nucl. Fusion 62, 096030], nonlinear simulations show that the ELM size of PFPO-2 is almost one-third of the grassy ELM, representing a distinct small ELM. However, simulations then show that if the PB instability is removed, the fluctuation amplitude drops by an order of magnitude and the ELM crash disappears, which is in accord with the theory in [Xu et al 2010 Physical Review Letters, Vol. 105, 175005] and the results in [Li et al 2022 Nucl. Fusion 62, 096030], confirming that the PB instability is a necessary condition for an ELM crash. Furthermore, removing the DAW drive also suppresses ELM crashes, implying that PB instability is necessary but insufficient for PFPO-2 ELM and that DAW could amplify PB-driven turbulence. In addition, by integrating results of both PFPO phases by BOUT++ turbulence analysis with heat flux width (λ q ) and electron thermal diffusivity (χ e ), these simulations establish a predictive framework for heat flux width and its dominant mechanisms, thereby providing a comprehensive scheme for the prediction of the heat flux width. Moreover, simulations indicate that DAW driving can increase the transport coefficient by enhancing the turbulent transport, leading to a broadened heat flux width once the transport coefficient exceeds
An array of small-area Silicon Drift Detectors (SDD), named Hera, has been developed at Brookhaven National Laboratory (BNL) in the past few years. Its primary application is high-rate spectroscopy at synchrotrons. Each SDD pixel is a 1 mm × 1 mm square to match the footprint of the original diode-based pixel detector called Maia, which was developed for the same application. The replacement of the diode with an SDD allows for better energy resolution at short shaping times and an increased stability of the detector. 32, 96, and 384-channel arrays were designed and fabricated and achieved a Full Width Half Maximum (FWHM) as low as 176 eV at 5.9 keV with peaking time of 1 μs at -13°C. The sensor design, simulation, fabrication, its readout system, and its spectroscopic performance are reported.
Tertiary modes in electrostatic drift-wave turbulence are localized near extrema of the zonal velocity U(x) with respect to the radial coordinate x. We argue that these modes can be described as quantum harmonic oscillators with complex frequencies, so their spectrum can be readily calculated. The corresponding growth rate $γ$ TI is derived within the modified Hasegawa-Wakatani model. We show that $γ$TI equals the primary-instability growth rate plus a term that depends on the local U''; hence, the instability threshold is shifted compared to that in homogeneous turbulence. This provides a generic explanation of the well-known yet elusive Dimits shift, which we find explicitly in the Terry-Horton limit. Linearly unstable tertiary modes either saturate due to the evolution of the zonal density or generate radially propagating structures when the shear |U'| is sufficiently weakened by viscosity. The Dimits regime ends when such structures are generated continuously.
The linear growth and nonlinear energy transfer of the electron drift instability (EDI) are experimentally measured in the plume of a low-temperature, Hall effect discharge. A frequency-based bispectral analysis technique applied to fast ion density fluctuation measurements shows a growth rate function that is qualitatively similar to predictions from the linear instability dispersion relation, but an order of magnitude smaller. Calculation of the nonlinear transfer function indicates multiple three-wave interactions between high-frequency resonances of the instability in addition to an inverse energy cascade toward lower-frequency modes. Furthermore, these results are discussed in the context of recent theoretical, numerical, and experimental efforts on the EDI in Hall effect discharges and how the EDI may impact anomalous cross field transport.
Tertiary modes in electrostatic drift-wave turbulence are localized near extrema of the zonal velocity $U(x)$ with respect to the radial coordinate $x$. We argue that these modes can be described as quantum harmonic oscillators with complex frequencies, so their spectrum can be readily calculated. The corresponding growth rate $\gamma_{\rm TI}$ is derived within the modified Hasegawa--Wakatani model. We show that $\gamma_{\rm TI}$ equals the primary-instability growth rate plus a term that depends on the local $U''$; hence, the instability threshold is shifted compared to that in homogeneous turbulence. This provides a generic explanation of the well-known yet elusive Dimits shift, which we find explicitly in the Terry--Horton limit. Linearly unstable tertiary modes either saturate due to the evolution of the zonal density or generate radially propagating structures when the shear $|U'|$ is sufficiently weakened by viscosity. The Dimits regime ends when such structures are generated continuously.