Particle Transport Research Articles

Upgrade of the Lyman-alpha diagnostic system on DIII-D for main chamber edge neutral studies.

The LLAMA (Lyman Alpha Measurement Apparatus) pinhole camera diagnostic had previously been deployed on DIII-D to measure radial profiles of the Lyman-α (Ly-α) deuterium neutral line brightness across the plasma boundary in the lower chamber to infer neutral deuterium density and ionization rate profiles. This system has recently been upgraded with a new diagnostic head, named ALPACA, that also encloses two pinhole cameras and duplicates the LLAMA views in the upper chamber. Similar to LLAMA, ALPACA provides two times 20 lines of sight, viewing the plasma edge on the inboard and outboard sides with a radial resolution of ∼2.5 cm (FWHM) and an effective time resolution of ∼1 ms that allows for the investigation of inter-ELM dynamics. The extended Ly-α system provides better coverage to study neutrals in experiments with various plasma shapes utilizing both the upper and lower divertors. Furthermore, post-campaign calibration of the LLAMA diagnostic has successfully been demonstrated for the first time. This was facilitated by various upgrades to the calibration set-up and detailed measurements of the emissivity distribution of the Ly-α calibration source using a pinhole collimator. It was found that the sensitivity of the inboard LLAMA pinhole camera was reduced by a factor of 2.0 ± 0.2 over the course of six months of plasma operation in 2021. The upgraded Ly-α system, equipped with improved absolute calibration, will provide key input for neutral fueling and pedestal particle transport studies and for 2D edge transport code validation on the DIII-D tokamak.

Flow structure around a microswimmer at fluid–fluid interface

Living organisms such as bacteria and algae often form biofilms at air–liquid and/or liquid–liquid interfaces. Therefore, it is important to understand the hydrodynamic interaction between the fluid–fluid interface and microorganisms. In the present study, a squirmer model is employed to study the flow field structures around a symmetrically trapped spherical microswimmer at an interface separating two fluids with viscosity contrast. In these simulations, Reynolds ( Re ) and Capillary ( Ca ) numbers are very small, and hence the contribution of inertia and interface deformations are neglected. The squirmer model is validated against the analytical solution obtained by considering a source dipole. It is observed that the flow structure and vorticity distribution around the microswimmers are strongly influenced by the squirmer parameter (β) and viscosity contrast (λ). Furthermore, the interplay between force-dipole and source-dipole along with viscosity contrast leads to a range of flow structures such as symmetric four-lobe and asymmetric quadrupolar flow fields. This flow structure asymmetry around the swimmer is quantified with different steady state orientations (φ). The effect of flow profile on the passive tracer particle transport is explored in terms of trajectories. Specifically, larger values of φ result in more profound curly trajectories.

Solute transport characteristics of columnar volumetric contraction networks with mega column structure and aperture variability

Numerical simulations explore for the first time the role of mega columns and aperture variability on particle transport through mature volumetric contraction networks as informed by a unique synthesis of network propagation and maturity. Columnar fracture patterns are generated by updating a series of Voronoi centers to the midpoint of a generated polygon over many iterations, creating 250 network realizations. A DFN simulator solves for fluid flow and tracks conservative particle trajectories within each network. Dominant fracture attributes impacting fluid flow and solute transport in volumetric contraction networks are fracture orientation, density, and aperture/transmissivity. Ensemble plume snapshots generated by networks with equal fracture transmissivity define a baseline-level of dispersion that is solely attributed to network structure and connectivity. Longitudinal and transverse dispersion increase and the center of plume mass becomes delayed relative to the baseline case when fracture transmissivity is varied according to a lognormal distribution. The incorporation of highly-transmissive, large-aperture mega column fractures leads to plume snapshots with a more pronounced leading edge and an order of magnitude faster average breakthrough times. The breakthrough curves contain three peaks reflecting contrasting transport pathways in which particles are: (i) initially placed in mega column fractures and remain in these features until exiting the model domain, (ii) initially placed into small column fractures, incur additional time to migrate and enter a mega column fracture, and remain within those mega columns, and (iii) initially placed in small column fractures and remain in these fractures. Incorporating variability in fracture transmissivity for both small column and mega column fractures disrupts the binary distinction between small column and mega column fracture velocities and leads to dispersed breakthroughs over long time scales with a single peak. These results demonstrate that preferential flow paths emerge in volumetric contraction networks due to contracts in fracture transmissivity, not fracture connectivity as observed in tectonic networks.

ATEP: an advanced transport model for energetic particles

In this paper we report on the implementation and verification of a phase-space resolved energetic particle (EP) transport model. It is based on a first-principle theoretical framework, i.e. the system of non-linear gyrokinetic equations and the related transport equations. Its focus is primarily directed toward understanding the meso-scale character of EPs and its consequences. Compared to the conventional description of thermal radial transport via a one-dimensional radial diffusion equation, the newly developed model is three-dimensional using canonical constants-of-motion (CoM) variables. The model does not assume diffusive processes to be dominant a priori, instead the EP fluxes are self-consistently calculated and directly evolved in CoM space. We use the EP-Stability workflow and the HAGIS code to determine the phase space fluxes explicitly either in the limit of constant mode amplitudes or an energy-conserving quasi-linear model. As an application of the model the transport of neutral-beam-generated EPs due to a toroidal Alfvén eigenmode in an ITER plasma is investigated. As there are no sources and collisions taken into account so far (for an extension of the model see the companion paper (Meng et al 2024 Nucl. Fusion accepted)), the results cannot be considered as an exhaustive study, but rather as a practical demonstration of the conceptual framework on the way to a comprehensive reduced description of burning plasmas.

Profiling of particulate matter transport flux based on dual-wavelength lidar and ensemble learning algorithm

Transport flux (TF) is a significant particulate matter (PM) characteristic. This paper introduces an advanced dual-wavelength polarization aerosol and wind lidar (Wind Flux 3000) capable of independently observing the PM TF. The PM TF observation capability, which allows for simultaneous aerosol and wind measurements, was achieved by integrating a Mie-polarization particle lidar module and a coherent Doppler wind lidar module into a single lidar system. The primary measurement products of the Wind Flux 3000 include particulate extinction coefficient at 532 nm and 1550 nm, volume linear depolarization ratio at 532 nm (δp,532), wind speed (WS), wind direction (WD), vertical speed (VS), turbulence intensity (TI) and mixing layer height (MLH), retrieved by physical and proven algorithms. The PM concentration scales with the measured optical parameters and is also impacted by other environmental or meteorological parameters. Under the framework of the potential relationship between the PM concentration and the above parameters, the PM2.5 and PM10 concentration retrieval models were established using the stacking method of the ensemble learning technique; the models were trained using the in-situ data as true values, while the signal-to-noise ratio (SNR) at 1550 nm, δp,532, WS, WD, VS, the standard deviation of VS, TI, MLH provided by the Wind Flux 3000, as well as the relative humidity and temperature from ERA5, the hours of the day, and a “dust day” flag were used as inputs. The R2, RMSE, and MAE for the comparison between the predicted and true values of the PM2.5 test set are 0.857, 13.52 µg · m- 3, 9.16 µg · m- 3, and those of the PM10 test set are 0.926, 24.75 µg · m- 3, 14.39 µg · m- 3, respectively. The performance of the PM2.5 and PM10 concentration retrieval ensemble models is better than that of individual machine learning algorithms and better than that of the linear model. On 15th March 2023, a strong southeastward dust transport process with dust plume deposition was observed at Qingdao by the Wind Flux 3000. The analyses of the dust event demonstrated the Wind Flux 3000's ability to evaluate the transports of PM quantitatively.

Energetic particles transport in constants of motion space due to collisions in tokamak plasmas

The spatio-temporal evolution of the energetic particles in the transport time scale in tokamak plasmas is a key issue of the plasmas confinement, especially in burning plasmas. In order to include sources and sinks and collisional slowing down processes, a new solver, ATEP-3D was implemented to simulate the evolution of the energetic particle (EP) distribution in the three-dimensional constants of motion (CoM) space. The Fokker–Planck collision operator represented in the CoM space is derived and numerically calculated. The collision coefficients are averaged over the unperturbed orbits to capture the fundamental properties of EPs. ATEP-3D is fully embedded in ITER IMAS framework and combined with the LIGKA/HAGIS codes. The finite volume method and the implicit Crank-Nicholson scheme are adopted due to their optimal numerical properties for transport time scale studies. ATEP-3D allows the analysis of the particle and power balance with the source and sink during the transport process to evaluate the EP confinement properties.

The impact of diffusiophoresis on hydrodynamic dispersion and filtration in porous media

It is known that the dispersion of colloidal particles in porous media is determined by medium structure, pore-scale flow variability and diffusion. However, much less is known about how diffusiophoresis, that is, the motion of colloidal particles along salt gradients, impacts large-scale particle dispersion in porous media. To shed light on this question, we perform detailed pore-scale simulations of fluid flow, solute transport and diffusiophoretic particle transport in a two-dimensional hyper-uniform porous medium. Particles and solute are initially uniformly distributed throughout the medium. The medium is flushed at constant flow rate, and particle breakthrough curves are recorded at the outlet to assess the macroscopic effects of diffusiophoresis. Particle breakthrough curves show non-Fickian behaviour manifested by strong tailing that is controlled by the diffusiophoretic mobility. Although diffusiophoresis is a short-time, microscopic phenomenon owing to the fast attenuation of salt gradients, it governs macroscopic colloid dispersion through the partitioning of particles into transmitting and dead-end pores. We quantify these behaviours by an upscaled analytical model that describes both the retention and release of colloids in dead-end pores and the observed long-time tailings. Our results suggest that diffusiophoresis is an efficient tool to control particle dispersion and filtration through porous media.

Highly variable deep-sea currents over tidal and seasonal timescales

Deep-sea transport of sediment and associated matter, such as organic carbon, nutrients and pollutants, is controlled by near-bed currents. On the continental slope, these currents include episodic down-slope gravity-driven turbidity currents and more sustained thermohaline-driven along-slope contour currents. Recent advancements in deep-sea monitoring have catalysed a step change in our understanding of turbidity currents and contour currents individually. However, these processes rarely operate in isolation and the near-bed current regime is still to be quantified in a mixed system. Such measurements are crucial for understanding deep-sea particulate transport, calibrating numerical models and reconstructing palaeoflow. Here we use 4 years of observations from 34 instrument moorings in a mixed system offshore of Mozambique to show that near-bed currents are highly dynamic. We observe spatial variability in velocity over tidal and seasonal timescales, including reversals in current direction, and a strong steering and funnelling influence by local seabed morphology. The observed near-bed currents are capable of mobilizing and distributing sediments across the seabed, therefore complicating deep-sea particulate transport and reconstruction of palaeoceanographic conditions.

Extended gamma-ray emission from particle escape in pulsar wind nebulae. Application to HESS J1809-193 and HESS J1825-137

There is growing evidence from gamma-ray observations at high and very high energies that particle escape is a key aspect shaping the morphological properties of pulsar wind nebulae (PWNe) at various evolutionary stages. We aim to provide a simple model for the gamma-ray emission from these objects including the transport of particles across the different components of the system. We applied it to sources HESS J1809$-$193 and HESS J1825$-$137. We developed a multi-zone framework applicable to dynamically young PWNe, taking into account the diffusive escape of relativistic electron-positron pairs out of the nebula into the parent supernova remnant (SNR) and their confinement downstream of the magnetic barrier of the forward shock until an eventual release into the surrounding interstellar medium (ISM). For a wide range of turbulence properties in the nebula, the GeV-TeV inverse-Compton radiation from pairs that escaped into the remnant can be a significant if not dominant contribution to the emission from the system. It may dominate the pion-decay radiation from cosmic rays accelerated at the forward shock and advected downstream of it. In the TeV-PeV range, the contribution from particles escaped into the ISM can exceed by far that of the SNR+PWN components. Applied to HESS J1809$-$193 and HESS J1825$-$137, we found that spatially extended GeV-TeV emission components can be accounted for mostly from particles escaped into the ISM, while morphologically more compact components above $50-100$ are ascribed to the PWNe. In these two cases, the model suggests high turbulence in the nebula and a forward shock accelerating cosmic rays up to $ at most. The model provides the temporal and spectral properties of the flux of particles originally energized by the pulsar wind and ultimately released in the ISM. It can be used to constrain the transport of particles in the vicinity of pulsar-PWN-SNR systems from broadband gamma-ray observations, or in studies of the contribution of pulsar-related systems to the local positron flux.

Effect of secondary flow and wall collisions on particle-laden flows in 90° pipe bends

Fully developed, statistically stationary particle-laden turbulent flows in a 90° pipe bend at a moderate Reynolds number are studied using direct numerical simulation coupled to a Lagrangian particle tracking technique. Three populations of particles are studied which are two-way coupled with the carrier phase. The focus is the investigation of the effect of strong curvature on particle transport dynamics across a range of particle inertias. A validation of the carrier phase predictions is performed, with good agreement found with available experimental data. It is demonstrated that the presence of particles notably affects the turbulence statistics of the carrier phase, decreasing the mean fluid velocity in the outer bend while slightly increasing it in the inner bend. Two intriguing phenomena emerge: the presence of a particle void near the inner bend and reflection layers near the outer bend. Centrifugal forces are responsible for driving particles to the outer wall, with some rebounding back into the main body of the flow, and others, influenced by the secondary flow in the plane of the pipe cross-section, converging towards the inner wall before re-entering the central pipe region. These effects dictate the size and shape of the particle void region and the formation of reflection layers due to particle-wall collisions. These two phenomena have a significant influence on the particle distribution in the pipe bend, as well as on the first- and second-order moments of the velocity and acceleration of the particulate phase. Finally, a heat map of particle-wall collision statistics indicates that the effect of the secondary flow on particle distribution and particle-wall collisions is not negligible.

Stokes drift in crossing windsea and swell, and its effect on near-shore particle transport in Lofoten, Northern Norway

Transport assessments near the coast are often related to particles drifting near the surface. Such “particles” may be salmon lice, cod eggs, macro plastics or ship debris. Their drift depends on the Eulerian currents and the Stokes drift associated with the wind-generated surface wave field. The Stokes drift must be parameterized, and in doing so, one will inevitably make bulk estimates of the direction and speed of the drift for the wave spectrum. This paper implements a recently proposed parameterization of the Stokes drift vertical profile, which accounts for the effect of swell and windsea that propagate in different directions, to the open-source Lagrangian particle tracking model OpenDrift. We investigate how particles drifting in the Lofoten archipelago in Northern Norway depend on the Stokes drift and how we parameterize it. The parameterization accounting for crossing windsea and swell leads to lower residence time near the coastline than other popular parameterizations in the domain we studied.

Experimental study on dynamics of a free-falling finite-size sphere associated with its collision with a wall in a boundary layer

To reveal the physical mechanisms of particle transport in the pneumatic and hydraulic transports, this study experimentally investigated the dynamics of a free-falling finite-size sphere associated with its collision with a wall and the surrounding flow field in a boundary layer flow. The simultaneous motion of finite-size sphere and its inducing flow field near the wall were measured by using a time-resolved particle image velocimetry. The results revealed that the free-falling velocity of sphere increases with Reynolds number before the first impaction, and then is almost unrelated to Reynolds number. The effect of gravity on sphere motion becomes weak with increasing Reynolds number. As the sphere approaches to the wall, the vortex appeared at the front of sphere moves to left side near the wall and reduces the sphere falling speed. After the sphere collided on the wall, the upward motion of sphere induces another vortex pair, which generates strong rotation of sphere.

A machine-learning augmented mixed method for simulating α particle transport in inertial confinement fusion

The plasma heating by the α particle transport is a main self-heating source in inertial confinement fusion (ICF) that determines the capsule implosion performance. Due to the high energy of α particle and the high temperature in the ICF capsule hot spot, significant non-equilibrium effect exists and the continuum mechanics breaks down. For the numerical simulation of implosion and charged particle transport, the Boltzmann equation needs to be solved to capture the kinetic effects. However, the 7-dimensional Boltzmann equation, the highly frequent Coulomb collision, and the multi-folded integral stopping power formulation greatly limits the computational efficiency and challenges the computational power. To overcome the high computational cost of high-frequent Coulomb collisions, we propose a mixed collision model according to which the collisions are categorized into low-frequent large-angle collisions and high frequent small-angle grazing collisions. The large-angle collision process is precisely solved based on the Coulomb cross-section. For the highly frequent small-angle grazing, a statistic model is constructed with second-order accuracy in time. The mixed collision model reduces the computational cost of scattering calculation by two orders of magnitude. For the multi-folded integral stopping power formulation, a neural network is used to improve computational efficiency. Based on the proposed algorithm, we develop one-dimensional to three-dimensional module code to directly solve the α particle transport Boltzmann equation. The α transport module code is integrated into the multi-physics LARED-S program. The MC version ICF software is verified by a simulation study of the N210207 and N191110 experiment.

Universal scaling in far-from-equilibrium quantum systems: An equivalent differential approach

Recent progress in out-of-equilibrium closed quantum systems has significantly advanced the understanding of mechanisms behind their evolution toward thermalization. Notably, the concept of nonthermal fixed points (NTFPs)-responsible for the emergence of spatiotemporal universal scaling in far-from-equilibrium systems-has played a crucial role in both theoretical and experimental investigations. In this work, we introduce a differential equation that has the universal scaling associated with NTFPs as a solution. The advantage of working with a differential equation, rather than only with its solution, is that we can extract several insightful properties not necessarily present in the solution alone. How the differential equation is derived allows physical interpretation of the universal exponents in terms of the time dependence of the amplitude of the distributions and their momentum scaling. Employing two limiting cases of the equation, we determined the universal exponents related to the scaling using the distributions near just two momentum values. We established a solid agreement with previous investigations by validating this approach with three distinct physical systems. This consistency highlights the universal nature of scaling due to NTFPs and emphasizes the predictive capabilities of the proposed differential equation. Moreover, under specific conditions, the equation predicts a power-law related to the ratio of the two universal exponents, leading to implications concerning particle and energy transport. This suggests that the observed power-laws in far-from-equilibrium turbulent fluids could be related to the universal scaling due to NTFPs, potentially offering insights into the study of turbulence.

Seasonal dynamics of airborne biomolecules influence the size distribution of Arctic aerosols

Organic matter is crucial in aerosol–climate interactions, yet the physicochemical properties and origins of organic aerosols remain poorly understood. Here we show the seasonal characteristics of submicron organic aerosols in Arctic Svalbard during spring and summer, emphasizing their connection to transport patterns and particle size distribution. Microbial-derived organic matter (MOM) and terrestrial-derived organic matter (TOM) accounted for over 90% of the total organic mass in Arctic aerosols during these seasons, comprising carbohydrate/protein-like and lignin/tannin-like compounds, respectively. In spring, aerosols showed high TOM and low MOM intensities due to biomass-burning influx in the central Arctic. In contrast, summer exhibited elevated MOM intensity, attributed to the shift in predominant atmospheric transport from the central Arctic to the biologically active Greenland Sea. MOM and TOM were associated with Aitken mode particles (<100 nm diameter) and accumulation mode particles (>100 nm diameter), respectively. This association is linked to the molecular size of biomolecules, impacting the number concentrations of corresponding aerosol classes. These findings highlight the importance of considering seasonal atmospheric transport patterns and organic source-dependent particle size distributions in assessing aerosol properties in the changing Arctic.

A Generic Implementation of the D1S Methodology for Dose Rate Assessment by Monte Carlo Codes in Fusion Applications

Dose rate assessment is of utmost importance in fusion reactors because of the maintenance operations that these facilities will require. The standard way to perform this assessment in ITER is use of the Direct 1-Step (D1S) methodology, which consists of performing neutron transport simulation, material activation, and decay photon transport simulation in one step and thus in one simulation only. Usually, implementation of the D1S methodology requires changing the source files in a reference Monte Carlo code. The purpose of the present work is to develop an easy-to-implement method for Monte Carlo codes to help calculate the dose rate in fusion reactors. To do so, the proposal is to act on nuclear data only and not on source files of the simulation codes. This is done by replacing prompt photon production in evaluation files by suitable decay photon production, taking into account radioactive decays of radionuclides and irradiation history. This study was to be applied first on the TRIPOLI-4® Monte Carlo code for the sake of simplicity. TRIPOLI-4 is the reference code for particle transport at CEA. The verification and validation process relies first on a comparison to the reference Rigorous 2-Step (R2S) methodology and then on an experiment, the so-called Frascati Neutron Generator (FNG) dose experiment. The nuclear database to be changed is of the ENDF-6 format, a recurrent format in neutronics studies. The analysis studied both neutron and photon responses to check if the simulation was performing normally in a physical way and to compare the results with references provided by simulations based on the R2S methodology or by the FNG dose experiment. The simulations have proven to be in good agreement with the experimental results.

Technical note: A GPU-based shared Monte Carlo method for fast photon transport in multi-energy x-ray exposures.

The Monte Carlo (MC) method is an accurate technique for particle transport calculation due to the precise modeling of physical interactions. Nevertheless, the MC method still suffers from the problem of expensive computational cost, even with graphics processing unit (GPU) acceleration. Our previous works have investigated the acceleration strategies of photon transport simulation for single-energy CT. But for multi-energy CT, conventional individual simulation leads to unnecessary redundant calculation, consuming more time. This work proposes a novel GPU-based shared MC scheme (gSMC) to reduce unnecessary repeated simulations of similar photons between different spectra, thereby enhancing the efficiency of scatter estimation in multi-energy x-ray exposures. The shared MC method selects shared photons between different spectra using two strategies. Specifically, we introduce spectral region classification strategy to select photons with the same initial energy from different spectra, thus generating energy-shared photon groups. Subsequently, the multi-directional sampling strategy is utilized to select energy-and-direction-shared photons, which have the same initial direction, from energy-shared photon groups. Energy-and-direction-shared photons perform shared simulations, while others are simulated individually. Finally, all results are integrated to obtain scatter distribution estimations for different spectral cases. The efficiency and accuracy of the proposed gSMC are evaluated on the digital phantom and clinical case. The experimental results demonstrate that gSMC can speed up the simulation in the digital case by ∼37.8% and the one in the clinical case by ∼20.6%, while keeping the differences in total scatter results within 0.09%, compared to the conventional MC package, which performs an individual simulation. The proposed GPU-based shared MC simulation method can achieve fast photon transport calculation for multi-energy x-ray exposures.

Three-Dimensional Structure of Human Epididymis Protein 4 (HE4): A Protein Modelling of an Ovarian Cancer Biomarker Through In Silico Approach

The Human Epididymis Protein 4 (HE4) biomarker has been extensively investigated for its potential in diagnosing ovarian cancer (OC). For the application of diagnostic techniques and drug delivery, it is crucial to understand the protein tertiary structure. However, the Protein Data Bank (PDB) does not currently contain the three-dimensional (3D) structure of HE4. Therefore, an in silico analysis was conducted to model the HE4 protein using AlphaFold, I-TASSER, and Robetta servers, with the sequence retrieved from UniProt (ID: Q14508). These three servers employed deep learning algorithms, threading templates, and de novo methods, respectively. Subsequently, Molecular Dynamics (MD) simulation using the GROMACS software package improved each 3D structure model, resulting in optimized and refined structures: RF1, RF2, and RF3. PROCHECK and ERRAT programs were employed to assess the structure quality. The Ramachandran plots from PROCHECK indicated that 100% of residues were within the allowed regions for all servers except for I-TASSER. For the refined structures, RF1 and RF3, all residues were concentrated within the allowed regions. According to the ERRAT program, the RF1 model exhibited the highest overall quality factor of 97.701, followed by RF3 and AlphaFold models with scores of 94.643 and 93.750, respectively. After these validations, RF1 emerged as the most accurately predicted 3D structure of HE4 and has one tunnel identified by CAVER 3.0 tool that facilitates the transportation of small particles to the active site, supported by FTsite and PrankWeb binding site predictions. This model holds potential for various computational studies, including the development of OC diagnostic kits. It will enhance our comprehension of the interactions between the protein and other biomolecules.

Mucus, airway and plume temperature effects on pMDI-drug delivery in a mouth-throat airway: Experimental and numerical studies

Effective pulmonary drug delivery through pressurized-metered dose inhalers (pMDIs) depends on accurately targeting pharmaceutical aerosols to specific lung areas. Achieving this necessitates a comprehensive understanding of airflow dynamics in the airway and particle transport mechanisms.In this study, a replica of the realistic geometry of the VCU medium-sized mouth-throat (MT) airway was fabricated by rapid prototyping (3D printing) to connect to a next-generation impactor (NGI) setup. The drug concentration deposited in the replica was measured at a constant flow rate of 30 L/min and room temperature using a high-performance liquid chromatography (HPLC) assay. This measurement validated our computational fluid dynamics (CFD) model for simulating particle transport under the same conditions. Large eddy simulation (LES) and discrete phase model (DPM) were employed to model the MT's airflow and particle transport. Using our CFD modeling, we focused on the effects of the temperature distribution of aerosol injection (plume), the influence of inlet air temperature, and the presence of the mucus layer on particle transport and deposition.Our findings revealed that decreasing the plume temperature from 10 °C to −54 °C reduced deposition by approximately 15%, although increasing the average deposited particle sizes within the MT by about 34.5%. The airflow pattern, affected by different plume temperatures, was the prevalent parameter in particle MT deposition. In contrast, the effect of different air inlet temperatures on deposition was negligible. Additionally, incorporating mucus layer features in CFD modelling could further modify the inhaler's efficiency by up to 11%, depending on the specific conditions like diverse plume temperature (−54 °C–10 °C) and airflow temperature conditions (−15 °C–45 °C).

An asymptotic preserving kinetic scheme for the M1 model of linear transport

Moment models with suitable closure can lead to accurate and computationally efficient solvers for particle transport. Hence, we propose a new asymptotic preserving scheme for the M1 model of linear transport that works uniformly for any Knudsen number. Our idea is to apply the M1 closure at the numerical level to an existing asymptotic preserving scheme for the corresponding kinetic equation, namely the Unified Gas Kinetic Scheme (UGKS) originally proposed in Mieussens (2013) and extended to linear transport in Xu and Huang (2010). A second order extension is suggested and validated. The generic nature of this method is also demonstrated in an application to the M2 model. Several test cases show the performances of this new scheme in both the M1 and M2 case.