Computational Particle Fluid Dynamics Research Articles

Transport and deposition of microplastics and nanoplastics in the human respiratory tract

Recent studies have unveiled the presence of nano- and microplastics (NMPs) within both human and avian respiratory systems, prompting an exploration into the interactions between these particles and the human respiratory system. Experimental evidence has strongly suggested that these plastic particles amplify human susceptibility to a spectrum of lung disorders, including chronic obstructive pulmonary disease, fibrosis, dyspnea, asthma, and the formation of frosted glass nodules. To advance the understanding, this study employs computational fluid-particle dynamics (CFPD) to study the transfer and deposition of poly-dispersed 1-100 nm nanoplastics and 1-100 μm microplastics under three breathing conditions. Notably, this investigation utilized a computerized tomography-based full respiratory tract model, comprehensively spanning regions from the nasal cavity to the 13th generation of the bronchial tree, providing a highly detailed representation of the anatomical complexities of the human respiratory system. The outcomes reveal distinctive deposition patterns of spherical, cylindrical, and tetrahedral NMPs in the human respiratory tract, elucidating the significant impact of breathing rate, pinpointing specific deposition hotspots, and highlighting the critical role of particle size in governing transport and deposition behavior. This study establishes a link between the behavior of nanoplastics within the respiratory tract and its consequential impact, providing insights that extend across three critical domains. Firstly, in environmental health, the research contributes to understanding NMP-related air pollution. Secondly, within respiratory medicine, the findings shed light on NMPs' role in respiratory disorders. Finally, this study guides the formulation of regulations addressing permissible NMP levels and mitigating associated health and environmental risks.

The swirl and pyrolysis reaction synergistically enhance solid-solid heat transfer and product separation in cyclone pyrolyzer

Cyclone pyrolyzer is a novel type of downer that combines centrifugal force field and double-layer cyclone vortex. Research on transfer behavior is helpful to optimize the pyrolyzer to meet the needs of pyrolysis. In this study, the Computational Particle Fluid Dynamics (CPFD) model is used to analyze the transfer behavior of binary particles, and finds that the swirl and reaction have a synergistic effect. This effect can increase the heating rate of the particles to the range of flash pyrolysis, and its mechanism lies in the flow field structure of the pyrolyzer. Due to the centrifugal force field, the particles gather to the near wall. The rapid swirl, which facilitates intense gas-solid heat transfer, leads to the rapid heating and pyrolysis of biomass particles. As the pyrolysis proceeds, the mass of the biomass particles becomes smaller and they are more easily affected by the gas flow in pyrolyzer. Under the action of gas flow, char particles serve as new heat carrier to form the inner cycle of particles, which strengthens the heating process. The pyrolysis products are discharged from the exhaust port in time with the flow field of the pyrolyzer to achieve separation from the heat carrier and inhibit the occurrence of secondary reactions.

Computational particle fluid dynamics simulation of gas–solid flow in a 3 MWth dual-circulation fluidized bed for chemical looping process

Regulation of gas–solid flow is crucial for optimizing the operation efficiency of dual-circulating fluidized beds that are considered to be the most appropriate type of chemical-looping reactors. Herein, a computational particle fluid dynamics method was employed to simulate the gas–solid flow in a 3-MWth dual-circulating fluidized bed used for chemical-looping combustion and gasification. The influence of structural difference between units on particle residence time was determined. The multi-parameter control mechanism of pressure, particle circulation, and particle residence time in a whole-loop system was investigated. Results revealed that under stable particle circulation, the particle residence time in the fuel reactor is much longer than that in the air reactor. The axial forces on the particles are reduced upon increasing particle density and size, leading to particle accumulation in the dense-phase zone. When the particle properties are stable, increasing the fluidizing gas flow rates by the same proportion leads to identical pressure drops on the involved two loop seals, which cause symmetrical alterations in the particle circulation rate between the air and fuel reactors. The dual-circulating fluidized bed exhibits certain multi-condition adaptability, which is limited by the stock bin volume. Overall, this study is beneficial for effective and economical optimization of the operation of chemical-looping dual-circulating fluidized beds.

A user-centered smart inhaler algorithm for targeted drug delivery in juvenile onset recurrent respiratory papillomatosis treatment integrating computational fluid particle dynamics and machine learning

Recurrent respiratory papillomatosis (RRP) is a chronic condition primarily affecting children, known as juvenile onset RRP (JORRP), caused by a viral infection. Antiviral medications have been used to reduce the need for frequent surgeries, slow the growth of papillomata, and prevent disease spread. Effective treatment of JORRP necessitates targeted drug delivery (TDD) to ensure that inhaled aerosolized drugs reach specific sites, such as the larynx and glottis, without harming healthy tissues. Using computational fluid particle dynamics (CFPD) and machine learning (ML), this study (1) investigated how drug properties and individual factors influence TDD efficiency for JORRP treatment and (2) developed personalized inhalation therapy using an ML-empowered smart inhaler control algorithm for precise medication release. This algorithm optimizes the inhaler nozzle position and diameter based on drug and patient-specific data, enhancing drug delivery to the larynx and glottis. CFPD simulations show that particle size significantly affects deposition fractions in the upper airway, emphasizing the importance of particle size selection. Additionally, optimal nozzle diameter and delivery efficiency depend on particle size, inhalation flow rate, and release time. The ML-based TDD strategy, employing a classification and regression tree model, outperforms conventional inhalation therapy by achieving a higher delivery efficiency to the larynx and glottis. This innovative concept of an ML-empowered smart inhaler represents a promising step toward personalized and precise pulmonary healthcare through inhalation therapy. It demonstrates the potential of AI-driven smart inhalers for improving the treatment outcomes of lung diseases that require TDD at designated lung sites.

CFPD-PK simulation of inhaled Delta-9-tetrahydrocannabinol aerosol dynamics: Transport, deposition, and translocation in a mouth-to-G10 subject-specific human airway

Medical cannabis is increasingly used as an alternative therapy for various conditions, including chronic pain, multiple sclerosis, epilepsy, and cancer-related symptoms. However, it is crucial to ensure that patients receive the intended dose of tetrahydrocannabinol (THC) from inhaled cannabis for optimal therapeutic effect without overdose risk. This requires a comprehensive understanding of the factors that influence the pharmacokinetics (PKs) of THC in the respiratory system. However, accurate estimation of lung dosimetry and blood concentration of inhaled THC remains challenging partially because the influence of diversified patient-specific puff patterns on inhaled THC transport, deposition, and translocation is still not well quantified. To address the knowledge gap mentioned above, this study employed a hybrid computational fluid-particle dynamics (CFPD) and PK model to evaluate factors that influence delivered doses of THC to the human respiratory system and the resultant THC-plasma concentration-time profile. Specifically, this study compared multiple puff waveforms for inhalation-holding-exhalation (IHE) with total puff volumes from 55 to 82 ml for 2 or 3 s, hold durations from 0 to 5 s, and three puff waveforms (i.e., square, sinusoidal, and realistic). THC deposition in the airways was recorded during all phases for each case using either 452,849 particles per second for the 1.128-μm monodisperse cases or 399,866 particles per second for the polydisperse cases, with the mass median aerodynamic diameter (MMAD) of 1.128 μm. Pulmonary air-THC particle flow transport dynamics, THC particle deposition data, and THC vapor absorption were predicted using CFPD for four airway regions, then scaled by region-specific bioavailability factors. The deposited THC mass in airway regions represents the initial mass entering a 3-compartment PK model, to predict the THC-plasma concentration-time profiles. The CFPD-PK results revealed significant variability in THC transport, deposition, and plasma concentration based on IHE factors. Specifically, larger puff volumes and longer holding times enhanced THC deposition in deeper airways and increased THC-plasma concentrations. Realistic transient puff waveforms predicted higher particle deposition and THC-plasma concentrations than simplified square waveforms. Polydisperse particle distributions show more realistic deposition patterns than monodisperse particle simulations. This study provides insights into the complexity of THC inhalation therapy, emphasizing the importance of considering individualized puff patterns and realistic particle size distributions in accurately predicting therapeutic outcomes, which is highly related to THC deposition in the lung and THC plasma concentration. These findings and the CFPD-PK modeling framework offer guidance for clinicians in prescribing personalized THC dosages, support regulatory science in evaluating inhalation devices, and contribute to ongoing research aimed at optimizing THC delivery for maximum therapeutic effectiveness while minimizing potential overdose risks.

The CPFD approach was used to investigate the particle flow characteristics and auxiliary air inlet in an ash transfer pipe

Numerical simulations for the air-solid two-phase flow in a horizontal pipe with a diameter of 125 mm and a length of 10 m were carried out using the Computational Particle Fluid Dynamics (CPFD) method. The deposition characteristics of particles in the pipe were investigated at various inlet flow rates and velocities, and the effect of the auxiliary inlet with different structural parameters on the evacuation of particles in the pipe after the auxiliary inlet was added to the horizontal pipe was compared. The results show that when the volume fraction of particles in the tube is less than 0.6, the flow of particles is relatively stable, and when the volume fraction of particles is greater than 0.8, the particles are seriously deposited and easily form a blockage; the auxiliary air inlet speed is proportional to the effect at the same tilt angle; when the air inlet speed is constant, the auxiliary air inlet angle increases from 35° to 55°, the effect of auxiliary air inlet increases and then decreases, and the effect of auxiliary air inlet reaches its peak at around 45°. The study's findings have implications for long-distance particle transport in horizontal pipelines.

Experimental and simulation studies of oxygen-blown, steam-injected, entrained flow gasification of lignin

This article presents results from experimental and simulation studies on a laboratory-scale pressurized O2-blown Entrained Flow biomass gasification Reactor (EFR) using pulverized commercial lignin pellets as feedstock. The primary focus lies in the assessment of the EFR’s performance indicators such as the H2/CO ratio, the Cold Gas Efficiency (CGE), and the Carbon Conversion Efficiency (CCE). The gasifier was operated at an absolute pressure of 8.2 bars, with varying amounts of O2 and steam. In the first series of experiments, the O2 equivalence ratio varied between 0.2 and 0.8, with no steam injection. This yielded a maximum CGE of 47%, a CCE of 94%, and an H2/CO ratio within the range of 0.4–0.7. In the last series of experiments, a perforated horizontal steam tube was installed allowing for a variation of the steam-to-biomass ratio (S/B), between 0.5 and 1.5. At a S/B of 1.5, the CGE and the CCE were at their highest levels of 91% and 99%, respectively. Based on the experimental setup, a 3D multiscale Eulerian-Lagrangian computational particle fluid dynamics (CPFD) model for the reactor was developed and validated against the experimental data. This model was then employed to explore the impacts of reactor temperature, S/B, equivalence ratio (λ), and the lignin particle size distribution (PSD) on the gasification process. The findings show that increased reactor temperature enhances H2 and CO production. Higher S/B ratios lead to greater H2 production but reduced CO production. Increased S/B ratios improve both CGE and CCE. Larger particles and higher λ values decrease CO and H2 production. Without steam injection, the peak CGE occurs at λ ≈ 0.45, corresponding to complete CH4 conversion. Beyond this point, as λ increases, reactor temperatures rise while CGEs decrease. Simulations reveal the optimal λ range for steam injection is 0.15–0.35. A sensitivity analysis highlights the significant impact of reactor temperature on H2 and CO production. While λ shows high sensitivity for H2 production, the S/B ratio exerts a greater impact on CO production.

A method for measuring the solid circulation rates of CFB boilers based on the particle flow-around principle

The solid circulation rate (Gs) is a key parameter for the design and operation of a circulating fluidized bed (CFB) industrial equipment, while the detection and measurement of the Gs value in an actual industrial CFB equipment remains difficult. To fill this gap, a method for the Gs measurement based on the flow-around principle was proposed in this study. The mathematical model for the signal transformation was established along the path “detected strain value – impact force – particle velocity – Gs value”, and the corresponding measurement device was also developed. The performance of the Gs measurement device was quantitatively validated in cold-state experiments and semi-quantitatively verified in an industrial trial in a CFB boiler. The results of a theoretical analysis indicate that the detected strain linearly increased with the impact force received by the intrusive spherical obstacle, and the slope coefficient was determined as per the experiment. The correlation of the impact force to the particle flow velocity was proposed and fitted using the experimental data. The computational particle fluid dynamics method was applied to simulate the particle flow field in the standpipe of the CFB boiler to determine the installation location of the Gs measurement device. The lab-scale cold-state experiments showed that the relative standard uncertainty of the Gs measurement using the device built in the present study was less than 2.0 %. This device was then applied in an industrial trial in a 116 MWth CFB boiler and the results proved the feasibility and applicability of the proposed Gs measurement method.

Artificial Intelligence for Hybrid Modeling in Fluid Catalytic Cracking (FCC)

This study reports a novel hybrid model for the prediction of six critical process variables of importance in an industrial-scale FCC (fluid catalytic cracking) riser reactor: vacuum gas oil (VGO) conversion, outlet riser temperature, light cycle oil (LCO), gasoline, light gases, and coke yields. The proposed model is developed via the integration of a computational particle-fluid dynamics (CPFD) methodology with artificial intelligence (AI). The adopted methodology solves the first principle model (FPM) equations numerically using the CPFD Barracuda Virtual Reactor 22.0® software. Based on 216 of these CPFD simulations, the performance of an industrial-scale FCC riser reactor unit was assessed using VGO catalytic cracking kinetics developed at CREC-UWO. The dataset obtained with CPFD is employed for the training and testing of a machine learning (ML) algorithm. This algorithm is based on a multiple output feedforward neural network (FNN) selected to allow one to establish correlations between the riser reactor feeding conditions and its outcoming parameters, with a 0.83 averaged regression coefficient and an overall RMSE of 1.93 being obtained. This research underscores the value of integrating CPFD simulations with ML to optimize industrial processes and enhance their predictive accuracy, offering significant advancements in FCC riser reactor unit operations.

Computational Particle Fluid Dynamics Simulation on Combustion Characteristics of Blended Fuels of Coal, Biomass, and Oil Sludge in a 130 t h−1 Circulating Fluidized Bed Boiler

In this study, the co-combustion of coal and biomass, and the tri-combustion of coal, biomass, and oil sludge in a 130 t h−1 circulating fluidized bed (CFB) boiler are investigated via the computational particle fluid dynamics (CPFD) approach. Furthermore, the effect of biomass feeding position is also comprehensively evaluated. The results show that for the co-combustion of coal and biomass, the O2 mole fraction at the furnace outlet rises from 0.0541 to 0.0640 as the biomass blending ratio enhances from 40% to 100%, while the CO2 mole fraction reduces from 0.1357 to 0.1267. The mole fraction of NOx and SO2 at the furnace outlet decreases from 4.5867 × 10−5 to 3.9096 × 10−5 and 2.8253 × 10−4 to 4.6635 × 10−5, respectively. For the tri-combustion of three fuels, the average NOx mole fraction initially grows quickly and then declines gradually, ranging from 4.1173 × 10−5 to 4.2556 × 10−5. The mole fraction of SO2 at the furnace outlet increases from 3.5176 × 10−4 to 4.7043 × 10−4 when the ratio of oil sludge rises from 10% to 20%. The uniformity of temperature and gas components distribution is “new inlet > secondary air inlet > feed inlet”. As for the three inlet positions, the mole fractions of NOx at the furnace outlet are between 3.9096 × 10−5 and 5.1537 × 10−5, while those for SO2 are between 2.5978 × 10−4 and 2.5278 × 10−4.

Numerical simulation on gas-solid flow during circulating fluidized roasting of bauxite by a computational particle fluid dynamics method

A full-cycle numerical simulation of a circulating fluidized bed (CFB) by the use of the computational particle fluid dynamics (CPFD) method has been developed. The effects of the presence or absence of the secondary air, different secondary air positions, and different secondary air ratios on the gas–solid flow characteristics were explored. The results show that the presence of the secondary air makes a core-annular structure of the velocity distribution of particles in the fluidized bed, which enhances the uniformity of particles’ distribution and the stability of fluidization. The position and the ratio of the secondary air have a significant impact on the particle distribution, particle flow rate, and gas flow rate in the fluidized bed. When the secondary air position and ratio are optimal, the particles, particle flow rate, and air flow rate in the CFB are evenly distributed, the gas–solid flow state is good, and the CFB can operate stably.

Numerical simulation and improvement of combustor structure in 3D printed sand recycling system

Abstract In this paper, a new combustor with an output of 5 t/h is designed based on a computational particle fluid dynamics (CPFD) model. The flow field simulation is combined with the combustion simulation to analyze the internal two-phase flow, temperature field, and combustion products. The combustor structure was optimized. The simulation results show that the recovery efficiency of the waste sand and the energy utilization of the combustor can be improved under the original structure. The sand bed has a significant effect on flow field characteristics. The increase in particle temperature in the combustor increases the efficiency of waste sand recovery by increasing the height of the sand bed by 50 mm. The utilization rate of natural gas is increased and the economic efficiency is improved. The feasibility of the CPFD method can simulate the flow field characteristics inside the combustor very effectively.

Numerical investigation of corticosteroid aerosol transport characteristics for pediatric acute epiglottitis at different severity levels

Inhalation therapy is widely used in the treatment of acute epiglottitis (AE). However, few studies specifically consider the anatomical variations in pediatric AE treatment. This study aims to evaluate the deposition pattern of inhalation corticosteroids (ICS) in realistic upper airway models of pediatric AE patients. The epiglottic angle increases with the severity of AE, and five models of epiglottic angle were constructed. The computational fluid-particle dynamics (CFPD) was employed to simulate the airflow transport of pediatric AE and the particle deposition in the target area. The results show that as AE progressed, worsened airway narrowing was observed in the epiglottis region, accompanied by a decreasing trend in the optimal ICS particle size. The deposition pattern of ICS in pediatric AE is closely linked to the disease severity. Furthermore, the airway resistance increases significantly at 75°AE, providing an aerodynamic basis for assessing the severity of laryngeal obstruction.

Numerical and experimental analysis of pollen inhalation exposure in nasal airways following various middle turbinectomy

BackgroundMiddle turbinectomy (MT) has always been controversial. MT significantly alters the anatomy and redistributes the inhaled air. The current study is designed to quantify the effect of MT with varying resection volumes on airflow and associated pollen inhalation exposure characteristics in the nasal airways. MethodsSix realistic models following bilateral comprehensive Functional Endoscopic Sinus Surgery (FESS) deriving from CT images were constructed and their corresponding post-MT models with four types of MT procedures were virtually conducted. Inhalation exposure to pollen particles was simulated by the Computational Fluid-Particle Dynamics (CFPD) approach and validated through in vitro experiments. ResultsFollowing the excision of the middle turbinate, a significant escalation in airflow was observed within the upper-middle region of the nasal cavities. Pollen deposition was observed to be more prominent in the nasal septum, laryngopharynx, and maxillary sinus, varying with the types of MT procedures. Notably, particles with diameters smaller than 50 μm exhibited two distinct “high peaks” and three “small peaks” within the nasal airways. ConclusionMT resulted in increased airflow volume within the upper-middle region of the nasal cavities. Following MT, notable shifts in pollen particle deposition hot spots were observed, transitioning from the nasal vestibule, nasal septum, and middle meatus to the nasal septum and laryngopharynx. These findings are anticipated to contribute valuable perspectives on pollen inhalation exposure risk assessments following diverse MT surgical interventions.

Numerical investigation of nanoparticle deposition in the olfactory region among pediatric nasal airways with adenoid hypertrophy

To understand inhaled nanoparticle transport and deposition characteristics in pediatric nasal airways with adenoid hypertrophy (AH), with a specific emphasis on the olfactory region, virtual nanoparticle inhalation studies were conducted on anatomically accurate child nasal airway models. The computational fluid-particle dynamics (CFPD) method was employed, and numerical simulations were performed to compare the airflow and nanoparticle deposition patterns between nasal airways with nasopharyngeal obstruction before adenoidectomy and healthy nasal airways after virtual adenoidectomy. The influence of different inhalation rates and exhalation phase on olfactory regional nanoparticle deposition features was systematically analyzed. We found that nasopharyngeal obstruction resulted in significant uneven airflow distribution in the nasal cavity. The deposited nanoparticles were concentrated in the middle meatus, septum, inferior meatus and nasal vestibule. The deposition efficiency (DE) in the olfactory region decreases with increasing nanoparticle size (1–10 nm) during inhalation. After adenoidectomy, the pediatric olfactory region DE increased significantly while nasopharynx DE dramatically decreased. When the inhalation rate decreased, the deposition pattern in the olfactory region significantly altered, exhibiting an initial rise followed by a subsequent decline, reaching peak deposition at 2 nm. During exhalation, the pediatric olfactory region DE was substantially lower than during inhalation, and the olfactory region DE in the pre-operative models were found to be significantly higher than that of the post-operative models. In conclusions, ventilation and particle deposition in the olfactory region were significantly improved in post-operative models. Inhalation rate and exhalation process can significantly affect nanoparticle deposition in the olfactory region.

Full-Loop Study of a Pilot-Scale Dual Fluidized Bed Cold Flow System: Hydrodynamic Simulation

Computational particle fluid dynamics (CPFD) simulations of three-dimensional cold-flow gas-solid flow were performed for a pilot-scale dual-circulating fluidized bed (DCFB) using Barracuda Virtual Reactor® 17.4.0. This DCFB system is a fluidized bed gasifier used in a calcium-loop gasification process to produce a hydrogen-rich gas with CO2 capture. The effects of different bubble bed inlet airflow rates and different solid inventories on the full-loop pressure distribution and particle concentration distribution were compared. The increase in the bubble bed inlet airflow rate significantly increases the pressure in the bubble bed and lift pipe, and the increase in the solids inventory significantly increases the pressure where the solids are tightly packed. For long-term operation, the appropriate combination of parameters should be found to maintain a stable particle seal at the loopseals.

Solar-driven biomass steam gasification by new concept of solar particles heat carrier with CPFD simulation

Solar-driven biomass gasification is a promising solar thermochemical technology to produce green H2-enriched syngas, and contribute to solar energy upgrade and efficient conversion. Whereas, the continuous and stable operation of solar-driven biomass gasification is challenging due to the non-uniform concentration of solar flux and its fluctuating nature. In this regard, a novel concept of solar-driven gasification is proposed, using solar-heated particles as the heat carrier, and biomass steam gasification in a fluidized bed reactor is numerically investigated based on the computational particle fluid dynamics (CPFD) model. The complex distributions of gas and particle phases, as well as the effects of operation parameters on syngas species are comprehensively analyzed. Results indicate that the biomass material and solar-heated particles can be well-mixed through continuous feeding, and the internal heat transfer and gasification kinetics are enhanced. The mole fraction of H2 and CO in the produced syngas reach to 50.86% and 18.97% under the benchmark operating condition. By using the high-temperature quartz sand as the solar particles heat carrier, the long-term and continuous operation of the endothermic gasification process can be achieved. The newly developed solar-driven biomass gasification method provides a promising approach to mitigate the impact of the fluctuating solar irradiation and enhance the operational flexibility of gasification process.

Modeling of inhaled corticosteroids delivery for topical croup treatment in pediatric upper airways

Croup is the most frequent cause of pediatric upper airway obstruction characterized by spindle-shaped stenosis in the subglottis mucosa. Inhaled corticosteroids (ICSs) serve as the first-line therapy for croup. Traditional ICS particles (1–4 μm in diameter) are primarily designed for trachea and lung diseases and show extremely low larynx deposition. Moreover, the specific correlation between airway minimal cross-sectional area (CSA) and airway resistance has not been fully understood. In this study, three healthy pediatric upper airway models with commercial nebulizer masks attached to their faces were reconstructed from computed tomography (CT) scans. Virtual mild, moderate, and severe croup were incorporated into these healthy models. To enhance the performance of conventional nebulizing drug delivery, the aerodynamic properties of croup with different degrees of stenosis were quantitatively analyzed, and the respiratory transit and deposition of ICS particles sized between 1 to 20 μm in our target area (glottis + subglottis) were modeled utilizing the Computational Fluid Particle Dynamics (CFPD) method. Results showed that in all models, maximum deposition fractions (DF) can be reached when the ICS particle sizes are 7–8 μm, and for particles sized at 8 and 9 μm, all models can achieve effective target area delivery (≥75% of the maximum DF), whereas the majority of traditional nebulizers produce smaller particles than what we recommended. Pediatric upper airway resistance is negatively correlated with the minimum airspace CSA (R ∝ CSA−1), which is in good agreement with the Bernoulli Obstruction Theory. Furthermore, when the constriction of the subglottis reaches a specific level (≥70% obstruction), the upper airway pressure drop abruptly surged and the dyspneic respiration symptoms of patients develop instantly.

A Pediatric Upper Airway Library to Evaluate Interpatient Variability of In Silico Aerosol Deposition

The airway of pediatric patients’ changes through development, presenting a challenge in developing pediatric-specific aerosol therapeutics. Our work aims to quantify geometric variations and aerosol deposition patterns during upper airway development in subjects between 3.5 months–6.9 years old using a library of 24 pediatric models and 4 adult models. Computational fluid–particle dynamics was performed with varying particle size (0.1–10 μm) and flow rate (10–120 Lpm), which was rigorously analyzed to compare anatomical metrics (epiglottis angle (θE), glottis to cricoid ring ratio (GC-ratio), and pediatric to adult trachea ratio (H-ratio)), inhaler metrics (particle diameter, {d}_{p}, and flow rate, Q), and clinical metrics (age, sex, height, and weight) against aerosol deposition. Multivariate non-linear regression indicated that all metrics were all significantly influential on resultant deposition, with varying influence of individual parameters. Additionally, principal component analysis was employed, indicating that {d}_{p}, Q, GC-ratio, θE, and sex accounted for 90% of variability between subject-specific deposition. Notably, age was not statistically significant among pediatric subjects but was influential in comparing adult subjects. Inhaler design metrics were hugely influential, thus supporting the critical need for pediatric-specific inhalable approaches. This work not only improves accuracy in prescribing inhalable therapeutics and informing pediatric aerosol optimization, but also provides a framework for future aerosol studies to continue to strive toward optimized and personalized pediatric medicine.Graphical

Time-scaled study on the erosion in circulating fluidized bed based on CPFD method

In this paper, the erosion characteristics in a circulating fluidized bed (CFB) were investigated on time scale with Euler-Lagrange model based computational particle fluid dynamics (CPFD). By analyzing average erosion rate data, two different erosion characteristics were found. In addition to the common linear erosion caused by downflow particles, another type of erosion is characterized by step growth and is caused by upwelling particles. Linear erosion at the height of 0.1 m is close to that at 0.2 m from the air distributor, but the value of stepped erosion at 0.1 m is much greater than that at 0.2 m. The simulation results show that stepped erosion is the main cause of erosion in the simulated object, accounting for about 70% of the total erosion. The present numerical study implies that the special gas-solid flow of CFB will bring different characteristics of erosion, and the anti-wear method should be targeted at the causes of erosion.