Forward Particle Research Articles

Research on flow field characteristics of curved pipe in bulk grain cyclone conveying based on gas solid coupling

AbstractIn the transportation of grain particles, elbow wear is a pressing concern. A novel approach to mitigate this involves introducing a lateral air supplement rotation mechanism that enables swirling transportation. We assessed the integration of this device at angles of 45°, 55°, and 65° to the central axis of the main pipeline. While the multiphase flow velocity within the main conduit was held constant at 20 m/s, the lateral device's airflow velocities were tested at 20, 30, and 40 m/s. Utilizing the CFD–DEM simulation for grain particle transportation around bends, our findings indicated that an optimal arrangement was with the lateral device at 55° relative to the main pipeline, with an airflow speed of 30 m/s. This setup fostered a forward particle spiral, drastically diminishing wear on the pipe wall. Experimental evaluations corroborated the simulation's outcomes.

Deep Entry of Low‐Energy Ions Into Mercury’s Magnetosphere: BepiColombo Mio’s Third Flyby Observations

AbstractAlthough solar wind‐driven convection is expected to dominate magnetospheric circulation at Mercury, its exact pattern remains poorly characterized by observations. Here we present BepiColombo Mio observations during the third Mercury flyby indicative of convection‐driven transport of low‐energy dense ions into the deep magnetosphere. During the flyby, Mio observed an energy‐dispersed ion population from the duskside magnetopause to the deep region of the midnight magnetosphere. A comparison of the observations with backward test particle simulations suggests that the observed energy dispersion structure can be explained in terms of energy‐selective transport by convection from the duskside tail magnetopause. We also discuss the properties and origins of more energetic ions observed in the more dipole‐like field regions of the magnetosphere in comparison to previously reported populations of the plasma sheet horn and ring current ions. Additionally, forward test particle simulations predict that most of the observed ions on the nightside will precipitate onto relatively low‐latitude regions of the nightside surface of Mercury for a typical convection case. The presented observations and simulation results reveal the critical role of magnetospheric convection in determining the structure of Mercury's magnetospheric plasma. The upstream driver dependence of magnetospheric convection and its effects on other magnetospheric processes and plasma‐surface interactions should be further investigated by in‐orbit BepiColombo observations.

Temperature Compensation for MEMS Accelerometer Based on a Fusion Algorithm.

This study proposes a fusion algorithm based on forward linear prediction (FLP) and particle swarm optimization-back propagation (PSO-BP) to compensate for the temperature drift. Firstly, the accelerometer signal is broken down into several intrinsic mode functions (IMFs) using variational modal decomposition (VMD); then, according to the FE algorithm, the IMF signal is separated into mixed components, temperature drift, and pure noise. After that, the mixed noise is denoised by FLP, and PSO-BP is employed to create a model for temperature adjustment. Finally, the processed mixed noise and the processed IMFs are rebuilt to obtain the enhanced output signal. To confirm that the suggested strategy works, temperature experiments are conducted. After the output signal is processed by the VMD-FE-FLP-PSO-BP algorithm, the acceleration random walk has been improved by 23%, the zero deviation has been enhanced by 24%, and the temperature coefficient has been enhanced by 92%, compared with the original signal.

A Hybrid Neural Network‐Based Improved PSO Algorithm for Gas Turbine Emissions Prediction

AbstractIn gas‐fired power plants, emissions may reduce turbine blade rotation, thus decreasing power output. This study proposes a hybrid model integrating the Feed forward Neural Network (FFNN) model and Particle Swarm Optimization (PSO) algorithm to predict gas emissions from natural gas power plants. The FFNN predicts gas turbine nitrogen oxides (NOx) and carbon monoxide (CO) emissions, while the PSO optimizes FFNN weights, improving prediction accuracy. The PSO adopts a unique random number selection strategy, incorporating the K‐Nearest Neighbor (KNN) algorithm to reduce prediction errors. Neighbor Component Analysis (NCA) selects parameters most correlated with CO and NOx emissions. The hybrid model is constructed, trained, and testedusing publicly available datasets, evaluating performance with statistical metrics like Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). Results show significant improvement in FFNN training with the PSO algorithm, boosting CO and NOx prediction accuracy by 99.18% and 82.11%, respectively. The model achieves the lowest MSE, MAE, and RMSE values for CO and NOx emissions. Overall, the hybrid model achieves high prediction accuracy, particularly with optimized PSO parameter selection using seed random generators.

Construction of GVR weight windows maps from very low density transport simulations

Fusion-related facilities present relevant neutron radiation fields even after penetrating through a considerable thickness of shielding material. Neutronic analyses performed via Monte Carlo codes, then, need Global Variance Reduction (GVR) techniques so that low statistical uncertainty is reached efficiently throughout the geometry.Mesh-based Weight Windows is a flexible methodology used extensively for variance reduction purposes, both for Local and Global Variance Reduction. Purely stochastic GVR methodologies based on Weight Windows usually construct weight maps so that they are proportional to the forward particle flux, which is unknown a priori. Therefore, an iterative cycle is established. In each iteration, a weight map is obtained from the forward flux that allows the next iteration to reach further into the geometry, until all of it is populated.However, this iterative cycle may take a considerable amount of computer time, as many iterations are needed to fully populate the geometry. An alternative to achieve relevant penetration in a single iteration is to perform calculations at very low densities. However, a reconstruction method is needed to estimate the flux at the real density. This work studies a scheme to reconstruct the fluxes from low density calculations and compares it to already existing techniques.

Incorporating a backward-forward stochastic particle tracking model into a hydraulic modeling framework to identify probable sedimentation sources during typhoons

Study regionShih-men Reservoir, Taiwan Study focusThe primary purpose of this research is to integrate the novel backward-forward stochastic particle tracking model (BF-SPTM) into a three-dimensional sediment transport model for the Shih-men Reservoir. This integration aims to simulate the distribution of sediment during typhoon events and effcientlyidentify probable sedimentation sources . Additionally, a Genetic Algorithm (GA) is developed to optimize the critical parameters of the EFDC hydrodynamic module and sediment transport module. New hydrological insightsIn the proposed BF-SPTM, the influence function is applied for the first time in a three-dimensional hydraulic model to integrate the backward and forward particle tracking processes, thereby providing more precise probable sources. In this study, a 'probable source' is considered a grid cell rather than a point, which substantially reduces the computational time in the BF-SPTM model. A case study using BF-SPTM during Typhoon MEGI demonstrates its capabilityto identify probable sources in natural water using the EFDC model. The output of the BF-SPTM can be effectively used to identify potential sources of sedimentation. Additionally, this study incorporated more realistic boundary and flow conditions from a natural river to enhance the practical application of BF-SPTM. These conditions included flow velocity, diffusivity, water surface, and bed topography.

The Forward Physics Facility at the High-Luminosity LHC

High energy collisions at the High-Luminosity Large Hadron Collider (LHC) produce a large number of particles along the beam collision axis, outside of the acceptance of existing LHC experiments. The proposed Forward Physics Facility (FPF), to be located several hundred meters from the ATLAS interaction point and shielded by concrete and rock, will host a suite of experiments to probe standard model (SM) processes and search for physics beyond the standard model (BSM). In this report, we review the status of the civil engineering plans and the experiments to explore the diverse physics signals that can be uniquely probed in the forward region. FPF experiments will be sensitive to a broad range of BSM physics through searches for new particle scattering or decay signatures and deviations from SM expectations in high statistics analyses with TeV neutrinos in this low-background environment. High statistics neutrino detection will also provide valuable data for fundamental topics in perturbative and non-perturbative QCD and in weak interactions. Experiments at the FPF will enable synergies between forward particle production at the LHC and astroparticle physics to be exploited. We report here on these physics topics, on infrastructure, detector, and simulation studies, and on future directions to realize the FPF’s physics potential.

Differentiating Nitrate Origins and Fate in a Semi-Arid Basin (Tunisia) via Geostatistical Analyses and Groundwater Modelling

Despite efforts to protect the hydrosystems from increasing pollution, nitrate (NO3−) remains a major groundwater pollutant worldwide, and determining its origin is still crucial and challenging. To disentangle the origins and fate of high NO3− (>900 mg/L) in the Sidi Bouzid North basin (Tunisia), a numerical groundwater flow model (MODFLOW-2005) and an advective particle tracking (MODPATH) have been combined with geostatistical analyses on groundwater quality and hydrogeological characterization. Correlations between chemical elements and Principal Component Analysis (PCA) suggested that groundwater quality was primarily controlled by evaporite dissolution and subsequently driven by processes like dedolomitization and ion exchange. PCA indicated that NO3− origin is linked to anthropic (unconfined aquifer) and geogenic (semi-confined aquifer) sources. To suggest the geogenic origin of NO3− in the semi-confined aquifer, the multi-aquifer groundwater flow system and the forward and backward particle tracking was simulated. The observed and calculated hydraulic heads displayed a good correlation (R2 of 0.93). The residence time of groundwater with high NO3− concentrations was more significant than the timespan during which chemical fertilizers were used, and urban settlements expansion began. This confirmed the natural origin of NO3− associated with pre-Triassic embankment landscapes and located on domed geomorphic surfaces with a gypsum, phosphate, or clay cover.

Radiation forces on a Mie particle in the evanescent field of a resonance waveguide structure.

Evanescent waves of a guided mode carry both momentum and energy, which enables them to move small objects located on a waveguide surface. This optical force can be used for optical near-field manipulation, arrangement, and acceleration of particles. In this paper, using arbitrary beam theory, the optical force on a dielectric particle in the evanescent wave of a resonance waveguiding structure is investigated. Using Maxwell's equations and applying the boundary conditions, all the field components and a generalized dispersion relation are obtained. An expression for the evanescent field is derived in terms of the spherical wave functions. Cartesian components of the radiation force are analytically formulated and numerically evaluated by ignoring the multiple scattering that occurs between the sphere and plane surface of the structure. Our numerical data show that both the horizontal and vertical force components and the forward particle velocity are enhanced significantly in the proposed resonance structure compared to those reported for three-layer conventional waveguides. Exerting stronger force on macro- and nanoparticles can be very useful to perform advanced experiments in solutions with high viscosity and experiments on biological cells. In addition, this resonance planar structure can be mounted on an inverted optical microscope stage for imaging the motion of nanoparticles especially when the particle collides and interacts with objects.

Versatile optical beam routers based on inversely designed supercell metagratings

Metagratings manipulating the wavefront with a subwavelength volume have been widely explored in recent years for their potential applications in optical beam routers, such as laser beam splitters and combiners. Current metagratings are hampered from practical beam rerouting due to inhibitive computational load of engineering design and expensive nanofabrication cost. In this work, we apply the emerging concept of supercell metagratings, which arranges random binary gratings of a unit cell in a one-dimensional periodicity, to simplify such design and fabrication processes. A high-performance inverse design framework for the supercell gratings is proposed. In such a framework, we use coupled wave algorithm as a fast-converging electromagnetic solver for the forward calculation and particle swarm optimization algorithm for the backward optimization. By manipulating the building blocks of a unit cell, specific diffraction orders of supercell gratings can be intentionally strengthened or eliminated. We finally realize high-efficiency, broadband and multi-functionality optical beam splitters and combiners both in visible and near-infrared regimes. We envision that the proposed method offers an avenue towards the mass production realization of flat optics.

Using Forward and Backward Particle Tracking Approaches to Analyze Impacts of a Water Intake on Ichthyoplankton Mortality in the Appomattox River

Municipal intakes of surface water have various uses, and their impacts on the aquatic environment and ecosystem, such as the impingement and entrainment of ichthyoplankton, are a major concern. A robust assessment of the intake impacts on ichthyoplankton in a system generally requires modeling efforts that can simulate the transport and dispersal pathways of the ichthyoplankton. However, it is challenging to simulate hydrodynamics with a high-resolution grid at the scale needed for intake screen sizes in a large system. In this study, a 3D unstructured grid model with a fine resolution grid (<1 m) was developed to investigate potential impacts of an intake on aquatic resources in a tidal freshwater estuary. This approach enables us to directly estimate intake-induced mortality. With the use of the coupled particle-tracking model, we evaluated the total and maximum daily removal rates of particles by the intake that can be used to estimate percent mortality of ichthyoplankton. We further investigated how impacts from the intake vary with spawning locations, flow conditions, and vertical migration velocity of ichthyoplankton. A risk assessment was conducted based on designed flow of water withdrawals. This approach is widely applicable and can address impacts of water intakes in other systems.

Kinematic constraint in the BFKL evolution near threshold region

We derive a modified Balitskii-Fadin-Kuraev-Lipatov equation with the rapidity veto that originates from external kinematic constraint. Though it is a formally subleading power contribution, such kinematic effect becomes very important in the threshold region, where there is no sufficient phase space for the small $x$ evolution to be fully developed. We also investigate the phenomenological consequences of the kinematic constraint Balitskii-Fadin-Kuraev-Lipatov equation in the forward particle production processes in pp and eA collisions. It is shown that particle yield at large transverse momentum is significantly suppressed in the threshold region.

Quantifying the Effects of Bed Roughness on Transit Time Distributions via Direct Numerical Simulations of Turbulent Hyporheic Exchange

AbstractWe report direct numerical simulation (DNS) results of hyporheic exchange for a flat river bed with two different particle roughness textures, at a surface flow friction Reynolds number of 395 and a bed permeability Reynolds number of 2.6. Transit time distributions (TTDs), subsurface flow patterns, and the interfacial volumetric fluxes are discussed. The transit time was quantified using a forward particle tracking method based on pure advection by three‐dimensional, pore‐resolved, time‐mean velocities. Results show that bed roughness induces deep subsurface flow paths that yield a TTD with a power‐law tail. Roughness obstructs the surface flow, creating interfacial pressure variations which induce subsurface flow. Next, the molecular diffusion is accounted for based on a random walk method and is shown to increase transit times regardless of roughness texture. This work demonstrates that particle roughness on a macroscopically flat sediment bed can induce significant hyporheic exchange that is fundamentally similar to that induced by bedforms.

Larval transport pathways from three prominent sand lance habitats in the Gulf of Maine

AbstractNorthern sand lance (Ammodytes dubius) are among the most critically important forage fish throughout the Northeast US shelf. Despite their ecological importance, little is known about the larval transport of this species. Here, we use otolith microstructure analysis to estimate hatch and settlement dates of sand lance and then use these measurements to parametrize particle tracking experiments to assess the source–sink dynamics of three prominent sand lance habitats in the Gulf of Maine: Stellwagen Bank, the Great South Channel, and Georges Bank. Our results indicate the pelagic larval duration of northern sand lance lasts about 2 months (range: 50–84 days) and exhibit a broad range of hatch and settlement dates. Forward and backward particle tracking experiments show substantial interannual variability, yet suggest transport generally follows the north to south circulation in the Gulf of Maine region. We find that Stellwagen Bank is a major source of larvae for the Great South Channel, while the Great South Channel primarily serves as a sink for larvae from Stellwagen Bank and Georges Bank. Retention is likely the primary source of larvae on Georges Bank. Retention within both Georges Bank and Stellwagen Bank varies interannually in response to changes in local wind events, while the Great South Channel only exhibited notable retention in a single year. Collectively, these results provide a framework to assess population connectivity among these sand lance habitats, which informs the species' recruitment dynamics and impacts its vulnerability to exploitation.

Tailoring the size of silver nanoparticles by controlling mixing in microreactors

Microreactors are commonly regarded by their high mass transfer rates associated to their small diameters. Although this is true, especially when compared to batch systems, mixing is frequently exclusively dominated by diffusion in single phase flow microreactors, being the fast mixing of reactants an aspect often overlooked during their design. This paper presents the first quantitative analysis of the effect of mixing of precursors on the size and distribution of metal nanoparticles synthesized in flow microreactors. Silver nanoparticles with a range of sizes are continuously synthesized by controlling mixing efficiency in rationally-designed microreactors. The particle size decreases as the mixing index increases due to an increase in nucleation rate and thus the resulting nuclei concentration. Herein, the mixing efficiencies of different 3D curved microreactors are quantitatively evaluated using accurate simulations of their concentration profiles, avoiding the so-called numerical diffusion errors using a novel method based on backward particle tracking. A method based on forward particle tracking is improved to simulate the residence time distributions (RTD) in microreactors at a reduced computational cost. Curving the reactors channels is known to lead to the formation of Dean vortices however, these well-defined rotations lead to stagnant zones. The mixing efficiency can be enhanced and the RTD narrowed by periodically changing the direction of the Dean vortices along the length of the channel. In addition, we demonstrate the effect of the configuration of the inlet streams relative to the curvature of the reactor and thus, the Dean vortices, on the resulting mixing. These results provide rational design guidelines for the design of microreactors to manipulate advection as a way of manipulating the reaction rates as demonstrated here to control nanoparticle sizes.

The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (nth-CASAM-L): II. Illustrative Application

This work illustrates the application of the nth-order comprehensive adjoint sensitivity analysis methodology for response-coupled forward/adjoint linear systems (abbreviated as “nth-CASAM-L”) to a paradigm model that describes the transmission of particles (neutrons and/or photons) through homogenized materials, as encountered in radiation protection and shielding. The first-, second-, and third-order sensitivities of responses that depend on both the forward and adjoint particle fluxes are obtained exactly, in closed-form, underscoring the principles and methodology underlying the nth-CASAM-L. The results presented in this work underscore the fundamentally important role of the nth-CASAM-L in the quest to overcome the “curse of dimensionality” in sensitivity analysis, uncertainty quantification and predictive modeling.

Change in spray behavior of pharmaceutical particles by creating bypass hole in dry powder inhaler

This study presents the effects of adding bypass holes in a dry powder inhaler on aerosol particle characteristics. A commercially available inhaler device was modified with bypass holes, and the resulting drug powder spray characteristics were investigated in terms of how the direction, size, and position of the bypass holes in the inhaler passage affect the spray output to find the optimal design. All three factors influenced the aerosol behavior, and in particular, it is most significantly affected by the direction of bypass hole faces. Adding bypass holes to the inhaler passage was found to decrease the mean penetration length of the drug particles by 12%; however, at the same time, the spray angle is increased by 35%, which leads to a significant decrease in forward particle momentum.

Stochastic Particle Tracking Application in Different Urban Areas in Central Europe: The Milano (IT) and Jaworzno (PL) Case Study to Secure the Drinking Water Resources

Urban areas are typically characterized by the presence of industrial sites, which are often sources of groundwater contamination, posing a serious threat for the groundwater. In such cases, a crucial step is to find a link between the contaminant sources and freshwater supply wells at risk. As a part of the AMIIGA Project, two different stochastic approaches were applied to assess drinking water supply wells vulnerability in Functional Urban Areas in the presence of several chlorinated hydrocarbons sources in an alluvial aquifer in Milano and a pesticide mega site in a complex geological setting in Poland. In the first case study, the innovative Pilot Point Null-Space Monte Carlo forward particle tracking was used, applying a forward solution instead of the classical backtracking, while in the second case was chosen the classical Monte Carlo methodology. Both case studies represent useful application examples, allowing an effective prioritization of expensive remediation actions in order to protect freshwater wells.

Small-Angle Particle Counting Coupled Photometry for Real-Time Detection of Respirable Particle Size Segmentation Mass Concentration.

Respirable particulate matter air pollution is positively associated with SARS-CoV-2 mortality. Real-time and accurate monitoring of particle concentration changes is the first step to prevent and control air pollution from inhalable particles. In this research, a new light scattering instrument has been developed to detect the mass concentration of inhalable particles. This instrument couples the forward small-angle single particle counting method with the lateral group particle photometry method in a single device. The mass concentration of four sizes of inhalable particles in the environment can be detected simultaneously in a large area in real-time without using a particle impactor. Different from the traditional light scattering instrument, this new optical instrument can detect darker particles with strong light absorption, and the measurement results mainly depend on the particle size and ignore the properties of the particles. Comparative experiments have shown that the instrument can detect particles with different properties by simply calibrating the environmental density parameters, and the measurement results have good stability and accuracy.

A mathematical model for predicting the flow behavior through a CFB reactor U type loop - seal

A mathematical model for predicting the flow behavior through a conventional U type loop-seal was developed by considering the loop-seal as a lumped system. The change rate of the gross forward particle flow rate (GG) with respect to the fluidization number at its bottom (Fn), GG', is assumed to be a function of the products of the gross forward particle flow rate coefficient (k) and the differential head across it. In addition, the flow resistance is considered as the virtual backward particle flow rate (Gr). Its change rate (Gr') is assumed to be a function of the products of the virtual backward flow coefficient (f) and the solid circulation rate provided by the loop-seal (Gs). The effects of the side aeration at the recycle side walls and heat exchanger in the chamber on the performance of the loop-seal was investigated. It was found that the relation between Gs and Fn is an asymptotic or a saturated function. From the regression analysis of the experimental data from a cold model circulating fluidized bed system according to the function, the function constants are obtained with the coefficient of determination of not less than 0.97. GG' is constant, while Gr' increases with Fn. The loop-seal with heat exchanger (LSHE) has a lower Gs. The LSHE with side aeration has a change rate of the forward particle flow rate with respect to Fn, and the virtual backward flow coefficient higher than the conventional loop-seal for the side aeration flow rate less than a certain value. After that, the opposite trend was found. The loop-seal having a higher fwill have a lower Fnor side aeration flow rate corresponding to saturated Gs. The developed model may be applied to any types and sizes of loop-seal and suggests that in order to have a high Gs, loop-seals should have their configuration provide a high gross forward particle flow rate coefficient (k) and a low virtual backward flow coefficient (f).