Drift Volume Research Articles

Study of charging-up of PCB planes for neutrino experiment readout

The use of double-faced, metallized, perforated PCB planes, segmented into strips for the anodic read-out of ionization signals in liquid argon TPCs, is emerging as a promising technology for charge readout in liquid argon TPCs used in large volume detectors.As a proof of concept, a prototype liquid Argon TPC hosting this new anode configuration based on single side perforated PCB planes has been constructed and exposed to cosmic rays at LNL in Italy. Tests were performed with both the metallized and insulating sides of the anode facing the drift volume, providing the first evidence of the focusing effect on drift electron trajectories through the PCB holes due to charge accumulation on the insulator surface.

Discovering outlying attributes of outliers in data streams

Data streams, continuous sequences of timestamped data points, necessitate real-time monitoring due to their time-sensitive nature. In various data stream applications, such as network security and credit card transaction monitoring, real-time detection of outliers is crucial, as these outliers often signify potential threats. Equally important is the real-time explanation of outliers, enabling users to glean insights and thereby shorten their investigation time. The investigation time for outliers is closely tied to their number of attributes, making it essential to provide explanations that detail which attributes are responsible for the abnormality of a data point, referred to as outlying attributes. However, the unbounded volume of data and concept drift of data streams pose challenges for discovering the outlying attributes of outliers in real time. In response, in this paper we propose EXOS, an algorithm designed for discovering the outlying attributes of multi-dimensional outliers in data streams. EXOS leverages cross-correlations among data streams, accommodates varying data stream schemas and arrival rates, and effectively addresses challenges related to the unbounded volume of data and concept drift. The algorithm is model-agnostic for point outlier detection and provides real-time explanations based on the local context of the outlier, derived from time-based tumbling windows. The paper provides a complexity analysis of EXOS and an experimental analysis comparing EXOS with existing algorithms. The evaluation includes an assessment of performance on both real-world and synthetic datasets in terms of average precision, recall, F1-score, and explanation time. The evaluation results show that, on average, EXOS achieves a 45.6% better F1 Score and is 7.3 times lower in explanation time compared to existing outlying attribute algorithms.

The DUNE Far Detector Vertical Drift Technology. Technical Design Report

DUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including themystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model.The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolutionrequired to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise.In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D.Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered.This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals.

Performance study of the Multi-purpose Time Projection Chamber (MTPC) using a four-component alpha source

The Multi-purpose Time Projection Chamber (MTPC) is a gas-filled detector designed to measure cross sections of neutron-induced light-charged particle emission and fission reactions at the Back-streaming white neutron facility (Back-n) at the China Spallation Neutron Source. A prototype MTPC has been constructed with a drift volume, a resistive Micromegas charge amplification structure, and a high-density pixelated anode readout plane with 1519 hexagonal pads. Test measurements have been performed using a four-component alpha source. Alpha-particle track reconstruction is performed to obtain the deposited energy and length information of the trajectory. The performance test and characterization of the detector have served as the basis for the optimized design of the MTPC, which is currently undergoing commissioning at Back-n.

GridHTM: Grid-Based Hierarchical Temporal Memory for Anomaly Detection in Videos.

The interest in video anomaly detection systems that can detect different types of anomalies, such as violent behaviours in surveillance videos, has gained traction in recent years. The current approaches employ deep learning to perform anomaly detection in videos, but this approach has multiple problems. For example, deep learning in general has issues with noise, concept drift, explainability, and training data volumes. Additionally, anomaly detection in itself is a complex task and faces challenges such as unknownness, heterogeneity, and class imbalance. Anomaly detection using deep learning is therefore mainly constrained to generative models such as generative adversarial networks and autoencoders due to their unsupervised nature; however, even they suffer from general deep learning issues and are hard to properly train. In this paper, we explore the capabilities of the Hierarchical Temporal Memory (HTM) algorithm to perform anomaly detection in videos, as it has favorable properties such as noise tolerance and online learning which combats concept drift. We introduce a novel version of HTM, named GridHTM, which is a grid-based HTM architecture specifically for anomaly detection in complex videos such as surveillance footage. We have tested GridHTM using the VIRAT video surveillance dataset, and the subsequent evaluation results and online learning capabilities prove the great potential of using our system for real-time unsupervised anomaly detection in complex videos.

Opportunities to Mitigate Particle Drift from Ground-Based Preemergent Herbicide Applications

Highlights Drift data collected from herbicide applications for corn, soybean, and cotton, including three commercial producers. Drift volumes and drift distances were estimated and correlated to wind speed, boom length, spray height, tractor speed, and droplet size (DV50). Boom length and spray height appear to be the dominant parameters affecting drift volume and drift distance, respectively. The results show a three- to fourfold reduction in drift using a hooded sprayer or spraying in calm weather. Abstract. Although several best practices are available, there are still opportunities to mitigate off-target pesticide drift, protect nearby sensitive crops, and address health concerns for humans/animals. The purpose of the study is to identify opportunities to mitigate drift from ground-based preemergent herbicide applications. Seven herbicide applications were tested for corn, soybean and cotton, including three regional commercial producers. Drift data were collected using water sensitive cards. ImageJ was used to analyze the droplet spectrum. Drift volumes and drift distances were estimated for each experiment. Data collected on wind speed, boom length, spray height, tractor speed, droplet size (DV50), and chemical application rate were used as explanatory variables of drift volume and drift distance. Individual and multiple linear regressions (MLRs) were carried out between drift volume, drift distance, and the explanatory variables. Our results show a three- to fourfold reduction in drift using a hooded sprayer or spraying in calm weather. Boom length and spray height appear to be the dominant parameters affecting drift volume and drift distance, respectively. The MLR results suggest that we can estimate drift (a) volume reasonably using a combination of boom length, DV50, and tractor speed and (b) distance reliably using a combination of spray height, boom length, and DV50. Keywords: Drift distance, Droplet spectrum, Fence board, Herbicide drift, Hooded sprayer, Preemergent herbicide, Water sensitive card.

Precision Variable-Rate Spraying Robot by Using Single 3D LIDAR in Orchards

Automatic navigation (AN) is an essential component to ensure the safety of pesticide application in orchards, whereas precision variable-rate spraying (PVS) serves as an indispensable technology for reducing the application of pesticides and protecting the environment. At present, AN and PVS are not closely combined. In this case, a single three-dimension (3D) light detection and ranging (LIDAR) sensor is hereby adopted to sense the information of fruit trees around the robot and determine the region of interest (ROI). Moreover, two-dimensional (2D) processing is conducted over the point clouds within the ROI to obtain the center-of-mass coordinates of fruit trees, and determine the vertical distance of the robot to the center line of the fruit tree row (FTR) based on the FTR on both sides using the Random Sample Consensus (RANSAC) algorithm. Then, the robot is controlled to drive along the center line of the FTR. At the same time, the speed and position of the robot are determined by the encoder and inertial measurement unit (IMU), and the IMU corrects the information collected from the zoned canopy of the fruit trees. The results present a lateral deviation (LD) of less than 22 cm and a course deviation (CD) of less than 4.02° during AN. Compared with the traditional spraying (TS), the PVS applies 32.46%, 44.34% and 58.14% less pesticide application, air drift and ground loss, respectively. With the spraying effect guaranteed, the single 3D LIDAR, the encoder and IMU realize the AN and PVS of the robot, reduce the volume of pesticide application, ground loss and air drift, and effectively control the pollution caused by pesticides to the environment.

Numerical Studies on Primary Ionization in TPC

Identification followed by directionality measurement using reconstruction of tracks is very crucial for studying the reaction vertex kinematics. In the field of low-energy nuclear physics, Active-Target Time Projection Chambers (AT-TPCs) can be used to study the nuclear reaction kinematics through tracking of the reaction products which is important for cross-section measurement. Ions produced in primary ionization by any charged particle along their track in the active gas volume of TPC can be utilized for track reconstruction with position-sensitive electron collection system placed inside an electric field. The TPC gas volume acts as the tracker of the reaction products and the target for the reaction with the incoming projectile simultaneously which is advantageous to conventional detector arrays. In this context, the design of the electric field in the drift volume of the TPC is an important criterion for precise tracking as the tracking capability of the TPC is strongly governed by the homogeneity of the electric field. Due to the lesser mobility of positive ions produced in primary ionization, their accumulation in the drift volume can distort the local electric field. In low-energy nuclear physics, this effect may be substantial due to the significant amount of ionization produced by the low-energy projectile and reaction products. Here we report the spatial information of primary space charges produced by cosmic muon and alpha particle obtained with geant4 [1] and Heed [2] simulation packages. We have used photo absorption and ionization physics lists in geant4 for the simulation and compared the results with that of the Heed. The simulation results for the change in pressure of gas volume will be reported. These results can be used for finding the distortion of the electric field due to the space charge in the drift region of the TPC which can be helpful for designing an AT-TPC for low-energy nuclear reaction experiments.

Deep neural network techniques in the calibration of space-charge distortion fluctuations for the ALICE TPC

The Time Projection Chamber (TPC) of the ALICE experiment at the CERN LHC was upgraded for Run 3 and Run 4. Readout chambers based on Gas Electron Multiplier (GEM) technology and a new readout scheme allow continuous data taking at the highest interaction rates expected in Pb-Pb collisions. Due to the absence of a gating grid system, a significant amount of ions created in the multiplication region is expected to enter the TPC drift volume and distort the uniform electric field that guides the electrons to the readout pads. Analytical calculations were considered to correct for space-charge distortion fluctuations but they proved to be too slow for the calibration and reconstruction workflow in Run 3. In this paper, we discuss a novel strategy developed by the ALICE Collaboration to perform distortion-fluctuation corrections with machine learning and convolutional neural network techniques. The results of preliminary studies are shown and the prospects for further development and optimization are also discussed.

Development of a time projection chamber for J-PARC hadron physics program

A time projection chamber (HypTPC) has been newly developed for the various hadron physics experiments at J-PARC. The design of HypTPC was carefully considered to cope with the J-PARC high intensity beam. The triple-layered GEM has been adopted as a signal amplification and the gating grid plane for an ion backflow suppression. The octagonal drift volume is defined by the cathode plane and the field cage structure with the height of 55 cm. A target is located inside the drift volume in order to have a large acceptance. The GET (General Electronic System for TPCs) is utilized for the data acquisition. The HypTPC was first commissioned with 230 MeV proton beam at HIMAC. The obtained position resolution is 400–700 µm, which gives the expected resolution of 230–300 µm under a magnetic field of 1 T. We have confirmed the high rate capability of the TPC up to 1 MHz with a good suppression of the ion backflow under the gate operation.

Diamond-Like Carbon for the Fast Timing MPGD

The present generation of Micro-Pattern Gaseous Detectors (MPGDs) are radiation hard detectors, capable of detecting effciently particle rates of several MHz/cm2, while exhibiting good spatial resolution (≤ 50 µm) and modest time resolution of 5-10 ns, which satisfies the current generation of experiments (High Luminosity LHC upgrades of CMS and ATLAS) but it is not sufficient for bunch crossing identification of fast timing systems at FCC-hh. Thanks to the application of thin resistive films such as Diamond-Like Carbon (DLC) a new detector concept was conceived: Fast Timing MPGD (FTM). In the FTM the drift volume of the detector has been divided in several layers each with their own amplification structure. The use of resistive electrodes makes the entire structure transparent for electrical signals. After some first initial encouraging results, progress has been slowed down due to problems with the wet-etching of DLC-coated polyimide foils. To solve these problems a more in-depth knowledge of the internal stress of the DLC together with the DLC-polyimide adhesion is required. We will report on the production of DLC films produced in Italy with Ion Beam Sputtering and Pulsed Laser Deposition, where we are searching to improve the adhesion of the thin DLC films, combined with a very high uniformity of the resistivity values.

Development of a GEM-based time projection chamber prototype for low-energy rare-isotope beam experiments

In this study, we developed a time projection chamber (TPC) prototype with gas electron multipliers (GEM) to evaluate the basic performance of the GEM-based TPC for the rare-isotope beam experiments to be conducted at the RAON heavy-ion facility. The TPC prototype has a drift volume of 10×10×15 cm3, and we operated it in an Ar/CH4 gas mixture (90/10). The TPC data acquisition system collected 256 pad signals in full-readout mode using cosmic-ray muons and α particles from an 241Am source. The measured spatial resolutions on the pad plane and along the drift direction were 350μm and 250μm, respectively. We also discussed the tracking performance of the future active target TPC with a 20 AMeV 12Be beam.

A New Concept for Kilotonne Scale Liquid Argon Time Projection Chambers

We develop a novel Time Projection Chamber (TPC) concept suitable for deployment in kilotonne-scale detectors, with a charge-readout system free from reconstruction ambiguities, and a robust TPC design that reduces high-voltage risks while increasing the coverage of the light-collection system and maximizing the active volume. This novel concept could be used as a far detector module in the Deep Underground Neutrino Experiment (DUNE). For the charge-readout system, we used the charge-collection pixels and associated application-specific integrated circuits currently being developed for the liquid argon (LAr) component of the DUNE Near Detector design, ArgonCube. In addition, we divided the TPC into a number of shorter drift volumes, reducing the total voltage used to drift the ionization electrons, and minimizing the stored energy per TPC. Segmenting the TPC also contains scintillation light, allowing for precise trigger localization and a more expansive light-readout system. Furthermore, the design opens the possibility of replacing or upgrading components. These augmentations could substantially improve the reliability and the sensitivity, particularly for low-energy signals, in comparison to traditional monolithic LArTPCs with projective-wire charge readouts.

Drag, deformation, and drift volume associated with a drop rising in a density stratified fluid

For a drop rising in a linearly density-stratified fluid, the drag acting on the drop, the drop deformation, and the drift volume induced are calculated. It is found that the stratification enhances the drag and reduces the drift volume, but it does not deform the drop.

Viscosity-Enhanced Fluid Drift around Hairy Structures

Hairy structures in nature function to sense smells and capture nutrients from surrounding fluid. Motivated by the complicated fluid transport processes observed in biological hairy structures, we numerically investigate the dynamics of fluid particles around multiple solid objects moving in a quiescent fluid, using simple two-dimensional cylinder models in the low-Reynolds-number regime ( R e = 1 –100). The behavior of fluid particles entrained by a moving cylinder array is analyzed by tracking particle trajectories and computing the drift volume, which indicates the amount of fluid particles transported by the moving cylinders. Hydrodynamic blockage of gaps within the cylinder array, which arises from the overlap of shear layers due to viscous diffusion, is critical in determining the overall fluid particle dynamics. As the number of cylinders increases, the deformation of the material line composed of fluid particles and the magnitude of the resultant drift volume show consistent patterns, despite undergoing drastic changes, and they converge to a specific configuration and magnitude, respectively. This study shows that visualization and quantification of collective fluid transport by multiple solid bodies are important to evaluate the efficiency of fluid transport for a collection of multiple bodies and to find its optimal configuration.

Spray Drift from Three Airblast Sprayer Technologies in a Modern Orchard Work Environment.

Pesticide spray drift represents an important exposure pathway that may cause illness among orchard workers. To strike a balance between improving spray coverage and reducing drift, new sprayer technologies are being marketed for use in modern tree canopies to replace conventional axial fan airblast (AFA) sprayers that have been used widely since the 1950s. We designed a series of spray trials that used mixed-effects modeling to compare tracer-based drift volume levels for old and new sprayer technologies in an orchard work environment. Building on a smaller study of 6 trials (168 tree rows) that collected polyester line drift samples (n = 270 measurements) suspended on 15 vertical masts downwind of an AFA sprayer application, this study included 9 additional comparison trials (252 tree rows; n = 405 measurements) for 2 airblast tower sprayers: the directed air tower (DAT) and the multi-headed fan tower (MFT). Field-based measurements at mid (26 m) and far (52 m) distances showed that the DAT and MFT sprayers had 4-15 and 35-37% less drift than the AFA. After controlling for downwind distance, sampling height, and wind speed, model results indicated that the MFT [-35%; 95% confidence interval (CI): -22 and -49%; P < 0.001] significantly reduced drift levels compared to the AFA, but the DAT did not (-7%; 95% CI: -19 and 6%; P = 0.29). Tower sprayers appear to be a promising means by which to decrease drift levels through shorter nozzle-to-tree canopy distances and more horizontally directed aerosols that escape the tree canopy to a lesser extent. Substitution of these new technologies for AFA sprayers is likely to reduce the frequency and magnitude of pesticide drift exposures and associated illnesses. These findings, especially for the MFT, may fit United States Environmental Protection Agency's Drift Reduction Technology (DRT) one-star rating of 25-50% reduction. An 'AFA buyback' incentive program could be developed to stimulate wider adoption of new drift-reducing spray technologies. However, improved sprayer technologies alone do not eliminate drift. Applicator training, including proper sprayer calibration and maintenance, and application exclusion zones (AEZs) can also contribute to minimizing the risks of drift exposure. With regard to testing DRTs and establishing AEZs, our study findings demonstrate the need to define the impact of airblast sprayer type, orchard architecture, sampling height, and wind speed.

Studies on ion back-flow of Time Projection Chamber based on GEM and anode wire grid

Gated wires are widely used in Time Projection Chamber (TPC) to avoid ion back-flow (IBF) in the drift volume. The anode wires can provide stable gain at high voltage with a long lifetime. However, switching on and off the gated grid (GG) leads to a dead time and also limit the readout efficiency of the TPC. Gas Electron Multiplier (GEM) foil provides a possibility of continuous readout for TPC, which can suppress IBF efficiently while keeping stable gain. A prototype chamber including two layers of GEM foils and anode wires has been built to combine both advantages from GEM and anode wire. Using Garfield++ and the finite element analysis (FEA) method, simulations of the transmission processes of electrons and ions are performed and results on absorption ratio of ions, gain and IBF ratio are obtained. The optimized parameters from simulation are then applied to the prototype chamber to test the IBF and other performances. Both GEM foils are run at low voltage (255V), while most of the gain is provided by the anode wire. The measurement shows that the IBF ratio can be suppressed to ~0.58% with double-layer GEM foils (staggered) at an effective gain about 2500 with an energy resolution about 10%.

Results From a Prototype Combination TPC Cherenkov Detector With GEM Readout

A combination Time Projection Chamber-Cherenkov prototype detector has been developed as part of the Detector R&D Program for a future Electron Ion Collider. The prototype was tested at the Fermilab test beam facility to provide a proof of principle to demonstrate that the detector is able to measure particle tracks and provide particle identification information within a common detector volume. The TPC portion consists of a 10x10x10cm3 field cage, which delivers charge from tracks to a 10x10cm2 quadruple GEM readout. Tracks are reconstructed by interpolating the hit position of clusters on an array of 2x10mm2 zigzag pads The Cherenkov component consists of a 10x10cm2 readout plane segmented into 3x3 square pads, also coupled to a quadruple GEM. As tracks pass though the drift volume of the TPC, the generated Cherenkov light is able to escape through sparsely arranged wires making up one side of the field cage, facing the CsI photocathode of the Cherenkov detector. The Cherenkov detector is thus operated in a windowless, proximity focused configuration for high efficiency. Pure CF4 is used as the working gas for both detector components, mainly due to its transparency into the deep UV, as well as its high N0. Results from the beam test, as well as results on its particle id capabilities will be discussed.

Assessment of sedimentation volumes of the shipping channel in the port of Arkhangelsk

Sedimentation is one of the natural negative factors limiting navigation and obliging to regularly carry out dredging. The navigable channel of the seaport of Arkhangelsk is significantly exposed by sedimentation processes, the annual volume of repair dredging is on average 1 million m³, which leads to environmental problems and economic costs. One of the tools for studying the sedimentation processes is the analysis of bathymetry and grain-size distribution of alluvial soils. The paper presents a quantitative assessment of the volume of a storm and the seasonal sediment accumulating regions of the ship channel of the seaport of Arkhangelsk in the example Mudyug, Solombala channels and the waters of the Bakaritsa handling area according to the digital models of the bottom topography, received during the annual hydrographic work from 2004–2017. The analysis of the grain-size distribution of alluvial soils in the water area of the selected objects was performed. It is established that on average precipitates about 200 thousand m3 of alluvial soil deposits on the Mudyug canal for one storm period. In addition, by constructing a regression model (coefficient of determination R2 = 0,682), a direct relationship between wind speed and storm drift volumes on the Mudyug chanmel was found. It is revealed that the maximum layer of alluvial soils is 275 cm, 67 cm and 65 cm during the seasonal period for the Mudyug, Solombala channel and the Bakaritsa, respectively, which are essential for the safety of navigation. The possible reasons for the accumulation and sources of alluvial soils for each zone in the seaport of Arkhangelsk are shown.

Spray Drift from a Conventional Axial Fan Airblast Sprayer in a Modern Orchard Work Environment.

Pesticide spray drift represents an important cause of crop damage and farmworker illness, especially among orchard workers. We drew upon exposure characteristics from known human illness cases to design a series of six spray trials that measured drift from a conventional axial fan airblast sprayer operating in a modern orchard work environment. Polyester line drift samples (n = 270; 45 per trial) were suspended on 15 vertical masts downwind of foliar applications of zinc, molybdenum, and copper micronutrient tracers. Samples were analyzed using inductively coupled plasma mass spectrometry and resulting masses were normalized by sprayer tank mix concentration to create tracer-based drift volume levels. Mixed-effects modeling described these levels in the context of spatial variability and buffers designed to protect workers from drift exposure. Field-based measurements showed evidence of drift up to 52 m downwind, which is approximately 1.7 times greater than the 30 m (100 ft) 'Application Exclusion Zone' defined for airblast sprayers by the United States Environmental Protection Agency Worker Protection Standard. When stratified by near (5 m), mid (26 m), and far (52 m) distances, geometric means and standard deviations for drift levels were 257 (1.8), 52 (2.0), and 20 (2.3) µl, respectively. Fixed effect model coefficients showed that higher wind speed [0.53; 95% confidence interval (CI): 0.35, 0.70] and sampling height (0.16; 95% CI: 0.11, 0.20) were positively associated with drift; increasing downwind distance (-0.05; 95% CI: -0.06, -0.04) was negatively associated with drift. Random effects showed large within-location variability, but relatively few systematic changes for individual locations across spray trials after accounting for wind speed, height, and distance. Our study findings demonstrate that buffers may offer drift exposure protection to orchard workers from airblast spraying. Variables such as orchard architecture, sampling height, and wind speed should be included in the evaluation and mitigation of risks from drift exposure. Data from our study may prove useful for estimating potential exposure and validating orchard-based bystander exposure models.