Real-time Particle Research Articles

Catalogue ofin situobserved solar energetic electrons from ACE/EPAM instrument

ABSTRACTWe present the first comprehensive catalogue of in situ observed solar energetic electron (SEE) events that covers solar cycles [SCs] 23 and 24 in the energy range 103–315 keV. The electron enhancements are detected by the Electron, Proton, and Alpha Monitor − Deflected Electrons instrument [EPAM-DE] aboard the ACE spacecraft. Onset time, peak time, background-subtracted peak electron intensity, and onset-to-peak fluence have been analysed for each event where possible. We describe the utilized procedure to identify the electron events and the criteria of their association to their solar origin: solar flares (SFs) and coronal mass ejections (CMEs). A statistical study between the peak electron intensity/fluence and the SF/CME properties, also with respect to the SC, is presented. In addition, we investigated the properties of the SEEs that are accompanied with solar energetic protons. Furthermore, the correlation between the intensity and fluence of the SEEs and those of the solar energetic protons are examined with respect to the SCs. The SEE catalogue is generated and posted on-line and will be updated whenever data are available. The purpose of this catalogue is to provide a publicly available service to solar and space physics communities. In addition, such catalogues are considered as a novel tool that can be used in real-time particle forecasting systems which are also relied upon to mitigate against harmful space weather effects due to particle events.

Characteristics of brake wear particle (BWP) emissions under various test driving cycles

The characteristics of brake wear particle (BWP) emissions were investigated under five driving cycles (WLTP, NEDC, FTP, 3h-LACT, and WLTP-Brake) with a brake dynamometer. The gravimetric method and real-time particle measurement instruments (APS, OPC, DustTrak, and QCM) were used to measure the BWPs. As a result, the mass concentrations of BWPs measured by APS were similar to the gravimetric method results. However, OPC and DustTrak underestimated the mass concentration of BWPs compared to the gravimetric method results. The QCM was unfavorable for measuring the BWPs because a significant number of particles abruptly inflowed into the QCM during a short moment of braking. The density of BWPs was observed to be larger than 1.0 g/cm3 because the optical mode diameter of the BWPs was smaller than the aerodynamic mode diameter. The BWP emissions were shown to be proportional to the brake dissipation energy and brake initial velocity of each driving cycle. Although the same dissipation energy was applied by braking, more BWPs were found to be emitted at high initial velocity condition. Because, BWPs already deposited on brake disc and pad was emitted as new generated BWPs at high initial velocity condition. When the value obtained by multiplying the dissipation energy by the 3.8th power of the initial velocity was compared to the PM emission of the BWPs, the correlation was more obvious than when only considering the dissipation energy.

Meso-Scale Kinematic Responses of Asphalt Mixture in Both Field and Laboratory Compaction

Compaction is one of the most critical steps in asphalt pavement construction. Traditional compaction relies heavily on engineering experience and post-construction quality control and can lead to under/over compaction problems. The emerging intelligent compaction technology has improved compaction quality but is still not successful in obtaining mixture properties of a single pavement layer. Besides, very few studies have discussed the internal material responses during field and laboratory compaction to explain the meso-scale (i.e., particle scale) compaction mechanism. Knowledge in those areas may greatly promote the development of smart compaction. Therefore, this study aims to investigate the kinematic behavior of the asphalt mixture particles (translation and rotation) under six types of field and laboratory compaction methods and establish the relationship between the field and the laboratory compaction by using a real-time particle motion sensor, SmartRock. It was found that particle movement pattern was mainly affected by the compaction mode. At the meso-scale where particle behavior is the focus, the kneading effects of a pneumatic-tire roller can be simulated by laboratory gyratory and rolling wheel compaction, and the vibrating effects of a vibratory roller can be simulated by Marshall compaction. However, none of those laboratory compaction methods can completely simulate the field compaction. Under vibratory rolling, particle acceleration decreased fast in the breakdown rolling stage. Under pneumatic-tire rolling, particle angular position change was related to aggregate skeleton, and particle relative rotation showed a decreasing trend that was consistent with the laboratory gyratory compaction results. Those kinematic responses can potentially be used to monitor density change in field compaction.

Accuracy comparison of fitting function applied to air-borne alpha detection spectrum

The ability to detect airborne alpha particles in real time could greatly enhance the safety of workers in radioactive environments. To assist in the development of an air-borne detection system, this study sought to overcome the difficulties in spectral analysis caused by the strong interaction of alpha particles with matter. Three modified Gaussian fitting functions were applied to a radon progeny alpha spectrum and cross-referenced to counteract the overlap phenomenon produced by low-tailing of the alpha peak. The radon progeny alpha spectrum was derived using MCNP6 and a PIPS (passivated implanted planar silicon) detector. The radionuclides were determined pertaining to two cases, where case 1 included 220Rn, 216Po, and 212Bi, and case 2 included 222Rn and 218Po. The RMS (root mean square) and reduced chi-square values were compared for accuracy. The convolution of an exponential low-energy tail with a Gaussian distribution equation provided 6.68% lower relative error than when two Gaussian distribution functions were combined according to centroid conditions. The relative error was 0.84% lower than with a Gauss function, indicating a spectrum-peak Gaussian distribution. By constructing the algorithm using this equation, it was possible to obtain high-accuracy analysis data even with low-resolution spectrums in the air.

Plutonium dioxide particle imaging using a high-resolution alpha imager for radiation protection

The internal exposure of workers who inhale plutonium dioxide particles in nuclear facilities is a crucial matter for human protection from radiation. To determine the activity median aerodynamic diameter values at the working sites of nuclear facilities in real time, we developed a high-resolution alpha imager using a ZnS(Ag) scintillator sheet, an optical microscope, and an electron-multiplying charge-coupled device camera. Then, we designed and applied a setup to measure a plutonium dioxide particle and identify the locations of the individual alpha particles in real time. Employing a Gaussian fitting, we evaluated the average spatial resolution of the multiple alpha particles was evaluated to be 16.2 ± 2.2 μmFWHM with a zoom range of 5 ×. Also, the spatial resolution for the plutonium dioxide particle was 302.7 ± 4.6 µmFWHM due to the distance between the plutonium dioxide particle and the ZnS(Ag) scintillator. The influence of beta particles was negligible, and alpha particles were discernible in the alpha–beta particle contamination. The equivalent volume diameter of the plutonium dioxide particle was calculated from the measured count rate. These results indicate that the developed alpha imager is effective in the plutonium dioxide particle measurements at the working sites of nuclear facilities for internal exposure dose evaluation.

Sensitive Monitoring Particles Conveying in Water Hydraulic System via a Facile Molding Conductive Hydrogel

Particles conveying in a liquid system is a major responsibility for triggering the erosion process. Understanding the motion track of particles is the key to take the following anti-erosion approaches in engineering application. The development of a simple, reliable, low-cost, and real-time particle detecting method for liquid flows has still been recognized as a challenge in hydraulic systems. As a kind of soft material, conductive hydrogels are widely used for intelligent devices, biomedical engineering, etc. However, at present, few results focus on the application of conductive hydrogel in hydraulic systems. This study explores the role of the conductive hydrogel in monitoring particles conveying the hydraulic system. We have prepared a novel and cheap sensor based on conductive hydrogel to monitor the particle information in water flow. From the real-time data, normal pressure, and particles monitor under complex conditions with different sand concentrations (4.9 wt.% and 10 wt.%), the conductive hydrogel-based monitor has a good performance on capturing particles conveying information in the hydraulic systems.

Comparison of travel time for particles with different route-choice methods in two-route traffic models

We explore the route-choice problem in two-route traffic systems when real-time particle densities are provided. Four scenarios are considered, which have three types of informed particle and two types of uninformed particle. They adopt different route-choice rules. The system is mimicked by a lattice model and each vehicle is supposed as a hard-core “particle”. With a macroscopic approach, the stability conditions of systems are theoretically analyzed, which separate long, intermediate and short travel time phases. The Monte Carlo simulation results certify theoretical predictions. The relative benefits of route-choice rules are compared by average travel times of different types of particles, which depend on system’s phases. These results are useful for traffic flow optimization on traffic networks.

Concentration and Composition in Subway Systems in the Northeastern United States.

Objectives:The goals of this study were to assess the air quality in subway systems in the northeastern United States and estimate the health risks for transit workers and commuters.Methods:We report real-time and gravimetric concentrations and particle composition from area samples collected in the subways of Philadelphia, Pennsylvania; Boston, Massachusetts; New York City, New York/New Jersey (NYC/NJ); and Washington, District of Columbia. A total of 71 stations across 12 transit lines were monitored during morning and evening rush hours.Results:We observed variable and high concentrations for on-train and on-platform measurements during morning (from 0600 hours to 1000 hours) and evening (from 1500 hours to 1900 hours) rush hour across cities. Mean real-time concentrations in underground stations were , , , , and for the PATH-NYC/NJ; MTA-NYC; Washington, DC; Boston; and Philadelphia transit systems, respectively. In contrast, the mean real-time ambient concentration taken above ground outside the subway stations of PATH-NYC/NJ; MTA-NYC; Washington, DC; Boston; and Philadelphia were , , , , and , respectively. Stations serviced by the PATH-NYC/NJ system had the highest mean gravimetric concentration, , ever reported for a subway system, including two 1-h gravimetric values of approximately during rush hour at one PATH-NYC/NJ subway station. Iron and total carbon accounted for approximately 80% of the mass in a targeted subset of systems and stations.Discussion:Our results document that there is an elevation in the concentrations across subway systems in the major urban centers of Northeastern United States during rush hours. Concentrations in some subway stations suggest that transit workers and commuters may be at increased risk according to U.S. federal environmental and occupational guidelines, depending on duration of exposure. This concern is highest for the concentrations encountered in the PATH-NYC/NJ transit system. Further research is urgently needed to identify the sources of and factors that contribute to high levels in individual stations and lines and to assess their potential health impacts on workers and/or commuters. https://doi.org/10.1289/EHP7202

Evaluation of different personalized ventilation air terminal devices: Inhalation vs. clothing-mediated exposures

Human exposure to particles indoors occurs through direct inhalation or indirectly through deposition on clothes that release them in other spaces. Ventilation systems are installed to decrease direct exposure but little is known about their effect on clothing-mediated exposures. This work weighs the effect of personalized ventilation (PV) systems on decreasing inhalation exposure to indoor particles versus their contribution to clothing contamination by particle deposition. To conduct this work, a 3D computational fluid dynamics model was developed for an office conditioned by mixing ventilation and common PV air terminal devices: computer mounted panel (CMP), vertical desk grill (VDG) and round movable panel (RMP). Typical particle sources were considered: furniture resuspension and human breathing. The model was validated experimentally in a climatic chamber by comparing real-time particle mass concentration near a thermal manikin. Results showed that CMP delivering 5 l/s reduced total inhalation exposure by 27% and deposition by 72% compared to standalone mixing ventilation. Increasing the flow to 10 l/s led to reductions of 89% in exposure and 56.5% in deposition. A VDG delivering 5 l/s reduced exposure by 33% while deposition reduction was negligible at 3%. Increasing the flow rate to 10 l/s reduced exposure by 91% and slightly increased deposition by 12%. The RMP at 5 l/s and 10 l/s reduced exposure by 89% and 97% respectively and increased deposition by 70% and 80% respectively. Among the three ATDs, the CMP offered the best compromise between reducing inhalation exposure and clothing-mediated exposures at all possible flow rates.

Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics.

Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as charged particle tracking, jet tagging, and clustering. An important domain for the application of these networks is the FGPA-based first layer of real-time data filtering at the CERN Large Hadron Collider, which has strict latency and resource constraints. We discuss how to design distance-weighted graph networks that can be executed with a latency of less than one μs on an FPGA. To do so, we consider a representative task associated to particle reconstruction and identification in a next-generation calorimeter operating at a particle collider. We use a graph network architecture developed for such purposes, and apply additional simplifications to match the computing constraints of Level-1 trigger systems, including weight quantization. Using the hls4ml library, we convert the compressed models into firmware to be implemented on an FPGA. Performance of the synthesized models is presented both in terms of inference accuracy and resource usage.

Application of a Diffusion Charger to Quantify Real-Time Particle Emissions from Light-Duty Vehicles: a Comparison Study with a Particle Size Spectrometer

Measurement methods for vehicle-emitted particulate matter (PM) have evolved as vehicle emission standards have become more stringent. For example, the filter-based gravimetric method has been demonstrated feasible to measure emissions at levels below 1 mg/mi from light-duty vehicles. However, while regulatory methods and instruments for measuring PM emissions are rigorous and accurate, there is a need to continue evaluating alternatives for use in the laboratory, as well as simple and robust instruments for screening that can be used for detecting high emissions on the roadside and evaluating the effectiveness of repairs in support of inspection and maintenance (I/M) programs. This study investigated the performance of an aerosol diffusion charger (TSI Electrical Aerosol Detector) by comparing its raw signal (aerosol active surface area) and its conversion to particle number and mass emission rates with those reported or calculated from a multi-channel electrometer-based particle size spectrometer (TSI Engine Exhaust Particle Sizer) and various condensation particle counters (CPCs). Four light-duty vehicles were tested, including gasoline port fuel injection (PFI), gasoline direct injection (GDI), and a diesel vehicle equipped with a diesel particulate filter (DPF). Results show that the diffusion charger was responsive over a wide particle size and concentration range, exhibiting sufficient signal-to-noise ratio during transient measurements of the gasoline PFI vehicle and light-duty diesel vehicle with a DPF (both certified below 1 mg/mi). High sensitivity at low concentrations suggests that the diffusion charger may have potential for identifying failures of emission control systems at lower concentrations than methods designed to report real-time suspended particle number or mass metrics directly. Systematic and fundamental data from our study underscore the challenge with “black box” equipment calibrated to calculate total particle number and mass from surface area measurements based on constant unimodal fit parameters. Future work could focus on the applications from deploying active surface area monitors at the roadside or for using surface area measurements to evaluate repair effective in support of I/M programs.

Effect of siderite dissolution on mineral particles interaction in aqueous suspension

Siderite dissolution and its effects on the interaction between siderite and quartz particle was investigated through focused beam reflectance measurement (FBRM) particle size analysis (a real-time particle characterization tool), zeta potential distribution measurement, and DLVO theoretical calculations, supplemented by dissolution tests, solution chemistry calculation, and X-ray photoelectron spectroscopy (XPS) analysis. The results of FBRM and zeta potential distribution measurement showed that the hetero-aggregation scarcely formed in the siderite-quartz mixture system, which was contrary with the calculated attraction energies (VTD) between siderite and quartz at pH 5.0. Dissolution test and solution chemistry calculation indicated that siderite could dissolve lattice ions, beside compression effects on the double electrode layer, the dissolved ferrous ions can also adsorb onto the negatively charged surface of quartz, which was confirmed by the results of zeta potential and XPS analysis. These would weaken the electrostatic attraction energies (VE) between siderite and quartz at pH 5.0, resulting in depressing the hetero-aggregation.

Soot Particle Agglomeration Inlet (SPAI) for Enabling Online Chemical Composition Measurement of Nanoparticles with the Aerosol Mass Spectrometer

Nanoparticles are a topic of interest because of their effects on human health and the climate, but the current options for evaluating their chemical composition—one of the key properties that determine the mechanisms of these effects—remain very limited and often require long collection times. For example, the Soot Particle Aerosol Mass Spectrometer (SP-AMS) is an instrument that measures the chemical properties of particles in real time, but sampling loss fixes its lower particle size limit at 50 nm, thus excluding nanoparticles. Hence, we developed the Soot Particle Agglomeration Inlet (SPAI), an addition to the SP-AMS that enables it to detect and analyze nanoparticles by attaching them to the surfaces of artificially generated soot particles. We characterized and optimized the soot generation and the soot–nanoparticle agglomeration via laboratory testing and then assessed the SPAI’s performance using silver nanoparticles as the test aerosol. The SPAI increased the SP-AMS’s capability to detect the silver nanoparticles by 35 times, demonstrating its potential in resolving issues related to analyzing the chemical composition of nanoparticles, either as an enhancement of the SP-AMS or as an addition to other sample pretreatment systems.

Effect of Pollution Level on Size Distributions and Mixing State of Ambient Black Carbon Particles in an Urban Area during Wintertime

We deployed a Single Particle Soot Photometer (SP2) and Single Particle Aerosol Mass Spectrometer (SPAMS) to investigate the size distribution and mixing state of ambient black carbon (BC) particles in Shanghai during the winter of 2017. The mixing state of the particles changed drastically under different meteorological conditions, and higher concentrations often occurred during haze episodes. The BC particles existed in two size modes: the condensation mode, which mainly consisted of fresh traffic-emitted particles, and the droplet mode, which encompassed heavily aged traffic-emitted particles, biomass burning particles and heavy-duty diesel engine emission particles. Whereas the heavily aged traffic-emitted particles exhibited relatively small BC cores (60–80 nm in diameter) surrounded by a thick coating (100–160 nm), the biomass burning particles displayed slightly larger cores (80–130 nm) covered by an even thicker layer (160–300 nm). However, we observed a large number of particles with large cores (150–200 nm) but a relatively thin coating (40–80 nm) on clean days. Trajectory analyses of the air masses showed that they usually originated in local areas or on the North China Plain during haze episodes but mostly migrated from the East China Sea during clean episodes. Interestingly, the BC particles in the clean air masses contained V more frequently and generated intense mass spectrum signals for Ca+, suggesting that these particles probably arose from heavy machinery emissions near ports. Our real-time single particle data indicates that the sources of BC aerosol can be easily identified by measuring the size distribution and mixing state of the particles.

Parametric optimization of unmanned vehicle controller by PSO algorithm

For an unmanned vehicle, in difficult conditions, when spatial constraints seriously narrow the space of admissible states, the strategy of choosing a state space is more effective than sampling in the control space. Although this was obvious, the practical question is how to achieve it while meeting the stringent constraints of the vehicle’s dynamic feasibility.This article presents an unmanned vehicle control system based on the predictive integrated path model (MPPI) controller, deep convolutional neural network (CNN) for real-time scene understanding and particle swarm optimization (PSO) to find the vector of optimal cost function parameters. The method is based on the optimization of the cost function, which determines where the vehicle should move on the surface of the path.

Near real-time magnetic particle imaging for visual assessment of vascular stenosis in a phantom model.

This study aimed to investigate the potential of magnetic particle imaging (MPI) to quantify artificial stenoses in vessel phantoms in near real-time. Custom-made stenosis phantoms with different degrees of stenosis (0%, 25%, 50%, 75%, and 100%; length 40mm, inner diameter 8mm, Polyoxymethylene) were filled with diluted Ferucarbotran (superparamagnetic iron-oxide nanoparticle (SPION) tracer agent, 500mmol (Fe)/l). A traveling wave MPI scanner (spatial resolution~2mm, gradient strength~1.5T/m, field of view: 65mm length and 29mm diameter, frequencies f1=1050Hz and f2=12150Hz) was used to acquire images of the phantoms (200ms total acquisition time per image, 10 averages). Standardized grey scaling was used for comparability. All measured stenoses (n=80) were graded manually using a dedicated software tool. MPI allowed for accurate visualization of stenoses at a frame rate of 5frames per second. Less severe stenoses were detected more precisely than higher-grade stenoses and came with smaller standard deviations. In particular, the 0%, 25%, 50%, 75%, and 100% stenosis phantom were measured as 3.7±2.7% (mean±standarddeviation), 18.6±1.8%, 52.8±3.7%, 77.8±14.8% and 100±0%. Geometrical distortions occurred around the center of the high-grade stenosis and led to higher standard deviations compared to lower grade stenoses. In the frame of this study the MPI signal depended linearly on the SPION concentration down to 0.05mmol (Fe)/l. Near real-time MPI accurately visualized and quantified different stenosis grades in vascular phantoms.

A Novel Impeded Flow Particle Receiver for Better Stability and Controllability

Various impeded flow particle receivers were proposed to prolong the particle residence time but always faced the risk of thermal deterioration and the difficulty of real-time particle velocity control. Herein, we reported a novel impeded flow particle receiver to solve above problems and further have the potential to control the particle velocity distribution. In this receiver, the friction along the path and the gate valves at outlet act as the obstruction structures to allow the particles to slide slowly and controllably in the form of a moving bed. The receiver’s structural validity and operational characteristics at different working conditions were detailly investigated with both experimental and numerical methods. Experimental results showed that the outlet particle temperature and efficiency could reach 847 o C and 77.2% under a solar simulator of 4 kW. An optical and thermal coupling model was developed and revealed an improved particle temperature of 1350 o C and efficiency of 82% under higher incident power. The effects of the temperature drop section, quartz glass on aperture and slow particle flow at the edge on the receiver performance were detailly analyzed, which could help optimize the design and operation of other particle receivers such as free-falling particle receivers.

Effect of angled spray nozzle designs on spray distribution and droplet spectrum

ABSTRACT New technologies have been developed to promote uniform, sustainable, safe and effective application of phytosanitary products. In this scenario, spray nozzles of different designs and jet angles can optimize application. Therefore, we aimed to analyze the effect of angled flat fan spray nozzles on spray pattern uniformity and droplet spectrum formation. The spray volumetric distribution of standard flat fan, double flat fan and the new angled flat fan spray nozzle, using two spray volumes were assessed. For that, the spray pattern distribution and the coefficient of variation (CV) were determined. The droplet spectrum characterization produced by the same treatments was performed in a real-time particle size analyzer. Also the effect of adding a fungicide mixture associated with an adjuvant on droplet formation was evaluated. All spray nozzles, regardless of design and spray volumes evaluated, produced CV values below 7%, considered acceptable by international uniformity standards. There was a difference in spray pattern according to the spray nozzle design and spray volume. It was evidenced that the main differences found in droplet spectrum occurred due to spray nozzle type, spray mixture and nominal flow rate, with little influence of spray jet angled or spray volumes.

Signal Encoder of Real-Time Bio-Aerosol Counter Using 280 nm UV-LED Induced Fluorescence

Real-time monitoring of bio-aerosols in the atmosphere has gained importance in both military and civilian security. As the first stage of defense architecture, a fluorescent particle counter is a compact, low-power, fast response sensor capable of giving a tentative warning. In this research, we developed a novel signal encoder for low power real-time fluorescent particle counter. Using a single 280 nm UV-LED light source and an acceleration nozzle, the particle counts are binned to three sizes: 0.84-2, 2-5, and 5- $11~\mu \text{m}$ . Integrated fluorescence is measured in 308–420 nm. Optimization of pulse width thresholds on the fluorescence channel based on fluorescent particle detection accuracy is demonstrated. Proposed size distinguishing scheme achieves accuracy of 0.853 compared to 0.823 for accuracy of single bin counterpart. The adaptive window scheme improves the dynamic range of particle counts. Further, the count efficiency improved by 0.394 for input count rate of 104 sec−1 compared to fixed size window scheme. Counting performance comparison with an APS validates good linearity of R2 = 0.984. As the device showcases high dynamic range, linearity, and detection accuracy, we expect that it can serve as a useful tool in ambient environment monitoring, especially concerning airborne fluorescent particles.

Long-term characterization of aerosol chemistry in cold season from 2013 to 2020 in Beijing, China.

Severe haze episodes in cold season in Beijing have been mitigated greatly during the last decade. However, the changes in aerosol chemistry as responses to the large reductions in gaseous precursors during the two phases of clean air action, i.e., phase Ⅰ (2013-2017) and phase Ⅱ (2018-2020), are less understood. Here we characterized such changes in cold season (January-March) by using five-year real-time aerosol particle composition measurements. Our results showed consistently large reductions for all chemical species from 2013 to 2020 with the largest decreases being chloride (95%) and organics (74%) followed by sulfate (69%), while the decreases in nitrate were comparatively small (44%). However, the contributions of sulfate were fairly stable despite the increased nitrate contributions from 18% in 2013 to 30% in 2020. Organic aerosol (OA) composition also changed significantly since 2018 with large increases in the contributions of secondary OA and corresponding decreases in primary OA from fossil fuel combustion and cooking emissions. The changes in aerosol chemistry were closely related to the different reductions in gaseous precursors, e.g., SO2 vs. NO2, and the enhanced secondary processes, e.g., the increases in O3, sulfur and nitrogen oxidation efficiency. Further, we found that the changes in aerosol chemistry in cold season during the phase Ⅱ of clean air action (2018-2020) started to slow down with relatively small changes in PM2.5 and secondary inorganic species. Our results point towards a future challenge in mitigating air pollution in cold season, and the need of more stringent and scientific strategies to control secondary aerosol pollution in an environment with enhanced oxidation capacity and high precursors.