Discrete Phase Research Articles

Numerical Analysis of Spray Evaporation Process in Desuperheater

Abstract The cooling water is sprayed into the desuperheater to regulate the temperature of the superheated steam. Computational fluid dynamics (CFD) was applied to investigate the spray evaporation process in the desuperheater. Discrete phase model (DPM) was applied to describe the gas-liquid two-phase flow characteristics based on the Eulerian-Lagrangian approach. The Rosin-Rammler distribution and TAB model were used for the description of the primary and secondary droplet breakup, respectively. The coupling effect of gas-liquid two-phase, influence of temperature on latent heat, the stochastic collision and coalescence of droplets were considered in the CFD model. The numerical results show good agreement with the plant data. The hydrodynamics and temperature distribution characteristics were analysed. The influence of water mass flow rate and orifice dimensions on temperature distribution and temperature non-uniformity was further investigated. The results indicate that increasing the water flow rate can improve the desuperheating ability, but it will make the temperature uniformity worse. Under the same operating conditions, smaller orifice diameters are beneficial for production of droplets with smaller size, leading to better desuperheating ability.

Assessing the effect of size and shape factors on the devolatilization of biomass particles by coupling a rapid-solving thermal-thick model

In CFD modeling, while the isothermal assumption has conventionally been coupled for updating particle temperature, its applicability diminishes when dealing with thermally thick particles. A thermal-thick discrete phase model (DPM) is developed to simulate pyrolysis of biomass particle group at high heating rates and temperatures, with particles tracked in a Lagrangian scheme. The effects of particle size and shape on the volatile release and heating history are investigated. For spherical particles with a diameter of 9.6mm, the temperature difference between the surface and center (∆T) does not disappear even up to 50seconds. In the particle size range spanning from 200 μm to 9.6mm, the duration required for a complete volatile release extends from 1.5 to 40s. For cylindrical particles, in contrast to the particles with an aspect ratio (AR, ratio of particle length to diameter) of 1, the devolatilization time of particles with an AR of 15 can be shortened by more than 50%. In addition, both the particle shape and size can significantly influence the volatile distribution within the reactor. This work contributes to understanding both the particle size and shape impact on heat and mass transfer during biomass pyrolysis at high heating rates.

Dynamics optimization of coupling atomization process in an injector achieved by novel micro laser powder bed fusion

This study employed large eddy simulation and a volume-of-fluid with discrete phase model to evaluate a swirl fuel injector's atomization performance. Addressing non-uniform atomization at low flow rates, the study optimized a swirl injector structure based on additive manufacturing advantages during re-modeling. Computational analysis revealed that vortex downstream and capillary bubbles caused non-uniformity in the prototype injector, mitigated by the optimized injector's three-dimensional flow channel. Comparative analysis showed similar parameters between the optimized and prototype injectors, except for significant improvement in circumferential uniformity at low flow rates (from 41.48% to 14.69%). The optimized injector's swirl structure, produced via micro laser powder bed fusion, exhibited precise dimensions and minimal surface roughness. Validation experiments without air inflow confirmed the computational results' reliability, with a minor discrepancy in circumferential uniformity (2.98%) and atomization cone angle (2.3°) for the prototype swirl structure. At low flow rates, the optimized structure showcased reduced circumferential non-uniformity (from 42.31% to 28.76%), underscoring its benefits. This interdisciplinary investigation underscores additive manufacturing's application in structural optimization and manufacturing.

Numerical simulations of polymer devolatilization in a steam contactor: Correlating particle distribution with volatile content removal

Abstract The focus of the current study is on a polymer devolatilization process in a device called a contactor, that involves the use of superheated steam to eliminate volatile cyclohexane, through evaporation, from the polymer mixture, also known as cement. The primary objective is to analyze the cement particle distribution and how it relates to the cyclohexane content at the exit or the devolatilization efficiency. The study develops a computational fluid dynamics (CFD) model that solves for the turbulent steam flow as a continuous phase and the the flow of cement droplets as a discrete phase. Following validation of the CFD model by comparing cement particle size distribution at the exit of the contactor to experimental data, a detailed examination of the same is conducted through a series of 69 CFD different calculations to understand its influence on the evaporation of the volatile in the polymer mixture. Two metrics are developed here: a cluster distribution index (CDI) based on the actual particle pairwise distances and a new mass-CDI based on the the radial distribution of masses. It is demonstrated that by relating the CDI and mass-CDI to the reduction in the cyclohexane content in the contactor, these metrics can be utilized to achieve the desirable input conditions in this polymer processing operation. Through a detailed examination of the particle dynamics in a steam contactor under various conditions, this study assists the polymer manufacturing industry in optimizing the devolatilization process for better steam savings and improved product quality.

The impact of different degrees of stenosis on platelet deposition in the left anterior descending branch of the coronary artery

Background and objectiveThis study aimed to investigate the impact of different stenotic degrees on platelet deposition in the left anterior descending branch of the coronary artery. MethodsThe idealized model of coronary artery stenosis of 30 %, 40 %, 50 %, 60 %, 70 % and four patient-specific models of 22.17 %, 34.88 %, 51.23 % and 62.96 % were established. A discrete phase model was used to calculate the deposition of platelet particles in blood. Results(1) As the stenotic degree increased from 30 % to 70 %, the maximum deposition rates were 4.23e-2 kg/(m2 ·s), 3.47e-2 kg/(m2 ·s), 0.14 kg/(m2 ·s), 0.15 kg/(m2 ·s), and 0.38 kg/(m2 ·s), respectively. (2) The greater the stenotic degree, the more points of platelet deposition. (3) Platelets were mainly deposited at the proximal segment of mild stenosis. When the stenotic degree exceeded 50 %, the deposition position moved to the distal segment of the stenosis. (4) The results in the real coronary artery models were similar to those in the idealized model. ConclusionThe study suggests that the location and number of platelet deposition are related to the degree of stenosis. Moderate to severe stenosis is more likely to spread downstream.

Analysis of Atomization Performance of Linear Laval Nozzle under Varied Water Pressures Based on VOF and DPM Models

Particulate matter from coal and stone operations is a primary air pollution source. The traditional nozzle requires high-pressure conditions, and the atomization droplets are large and uneven. This paper aims to study a linear Laval nozzle and investigate the impact of water pressure on atomization performance. The volume of fluid (VOF) model and discrete phase model (DPM) of Fluent are used to simulate the internal and external fields of the nozzle and analyze the velocity, droplet size, and atomization angle. The results show that the optimized water pressure parameters are 0.1 MPa with an air pressure of 0.5 MPa. Droplets in the middle are smaller, while those on the sides are larger. Compared to traditional nozzles, the water pressure is reduced by over 90%, and the Sauter mean diameter (SMD) decreases by over 50%. Moreover, the theoretical spray angle increases by approximately 150%.

Mathematical Modeling on the Multiphase Flow during Top–Bottom Combined Blowing Basic Oxygen Furnace Steelmaking Process

A 3D mathematical model on the multiphase flow and splashing phenomenon in a 210 t Basic oxygen furnace converter is established. The turbulent multiphase flow of the molten steel, slag, and oxygen is simulated by the combined realizable k−ε model and volume of fluid model. The trajectory of argon bubbles and the interaction between the molten steel and argon is simulated by the two‐way coupled Lagrangian discrete phase model. Effects of the lance height and bottom‐blowing gas flow rate on the multiphase flow and splashing phenomenon are investigated. The results indicated that the cavity depth is decreased from 0.45 to 0.36 m when the lance height increases from 1700 to 2300 mm. The cavity depth is not significantly affected by the bottom‐blowing argon flow rate with the 44 000 m3 h−1 top‐blowing oxygen flow rate and 1700 mm lance height. The increased lance height resulted in a decrease in splashing. When the oxygen lance height increases from 1700 to 2300 mm, the amount of the splashed molten steel decreases from 3774.3 to 1953.0 kg.

Coupled Discrete Phase and Eulerian Wall Film Models for Drug Deposition Efficacy Analysis in Human Respiratory Airways.

The current study explores the effectiveness of drug particle deposition into human respiratory airways to cure various pulmonary-bound ailments. It has been assumed that drug solutions are inhaled in the form of tiny droplets or mist, which after striking create a thin layer along the inner surface of airways where the virus initially resides to infect the human body. A coupled Eulerian wall film (EWF) and discrete phase model (DPM) based simulation approach is used to capture these dynamics. Here, the Lagrangian DPM technique tracks the dynamics of tiny droplets, while the liquid layer formation after striking is captured using the Eulerian thin film approximations or the EWF model. Previous studies in this field primarily employed only the DPM method, which is inadequate to predict the poststriking dynamics of drug layer deposition and their spread to neutralize the respiratory virus. The drug delivery effectiveness is characterized by three different particle sizes, 1, 5, and 10 μm at the inhalation rates of 15, 30, and 60 L per minute (LPM). It has been found that the size of the drug particles significantly influences drug delivery effectiveness. The film thickness increases monotonically with particle sizes and inhalation rates. However, this increase in averaged film thickness is prominent in the range 5 to 10 μm (≈60%) compared to 1 to 5 μm (≈10%) droplet sizes at generation level 4 (G4). The other deposition parameters, e.g., deposition fraction, deposition density, and area coverage) roughly show similar behavior with the increase in droplet sizes. Therefore, it is recommended to vary the droplet sizes between 5 and 10 μm for better deposition effectiveness. The sizes of more than 10 μm mostly stuck into the oral cavity and cannot reach the targeted generations. In contrast, less than 5 μm may reach much deeper generations than the targeted one.

Numerical simulation of the impact of rainfall on tunnel fire

An improved understanding of tunnel fire dynamics is crucial for fire and life safety. This work highlights the significance of Computational Fluid Dynamics (CFD) techniques in addressing the interaction between tunnel fires and rainfall. The discrete phase model based on the Lagrangian approach is applied to simulate raindrops, while the species transport model is used to simulate fuel combustion. A numerical model is established to investigate the impact of rainfall on tunnel fires, and the correctness of the model is verified by comparing the results to model-scale tunnel experiments. Results show that the raindrops increase the local pressure in the rainfall area, creating a pressure difference between the rainfall tunnel portal and the no-rain portal, which leads to longitudinal airflow inside the tunnel. This rain-induced airflow prevents smoke from moving toward the rainfall tunnel portal and decreases the smoke height near the no-rainfall portal. Correlations between the local increased pressure, induced-airflow velocity, and rainfall parameters are proposed. Besides, the model is scaled up to full-size, and real-scale tunnel fires under the influence of rainfall are evaluated. Findings draw attention to tunnel fire dynamics under extreme weather conditions for improved fire safety and evacuation strategies.

Evaluating the impact of human movement-induced airflow on particle dispersion: A novel real-time validation using IoT technology

Human movement significantly influences local airflow and particle dispersion in indoor environments. Therefore, this study integrates the dynamics of human walking into the analysis of airborne infection risks in a positive pressure isolation ward designed for the protection of immunocompromised patients. Real-time data collection was performed using an anemometer and IoT-based PM sensors to measure airflow velocities and particulate matter (PM) concentrations within a full-scale experimental chamber. Computational Fluid Dynamics (CFD) was used for the numerical simulations, and a User-Defined Function (UDF) code simulated the translational movement of a manikin. The results demonstrated strong agreement with the experimental data, thereby validating the airflow turbulence and Lagrangian-based Discrete Phase Model (DPM) in predicting the airflow velocities and particle transport. The study revealed that human walking substantially enhanced particle dispersion distance by 10-fold compared to static conditions, primarily attributed to intensified air mixing induced by the body movement. Furthermore, the CFD analysis underscored that the direction of walking plays a crucial role in airborne transmission. Specifically, walking away from a patient did not elevate infection risk, whereas approaching a patient significantly increased particle deposition in the patient-occupied region. This study highlights the critical need to consider both movement patterns and directional flow in managing airborne infection risks, contributing to the development of more effective infection control strategies in healthcare settings.

Research on factors affecting bubble and particle behavior in a three-phase flotation system based on COMSOL

ABSTRACT To investigate the impact of various parameters on bubble and particle dynamics in a flotation system, COMSOL software was utilized. The “two-phase flow – Level Set” module coupled with the “fluid particle interaction” module was used to explore the behavior of single bubbles and particle groups. The bubbles were set as a discrete phase to represent a group of floating bubbles. By combining the “Single-phase flow” module with dual “fluid-particle interaction” modules, we examined the interactions between bubble populations and particles within the system. The research results show that as the bubble diameter increases, the carrying effect of the bubbles on the particles becomes stronger. When the bubble radii are 1, 1.25, 1.5, 1.75, and 2 mm respectively, the maximum movement speed of the particles in the area increases by 3.0%, 2.3%, 5.1%, and 2.7%. The average speed of the particles increases by 7.9%, 7.3%, 9.0%, and 10.0%. Increasing the mass flow rate can increase the collision probability between particles and bubbles, thus increasing the flotation rate. However, a too high mass flow rate will make the state of bubbles unstable. When the mass flow rate is less than 1.5 kg/s, the bubbles remain stable. When the mass flow rate exceeds 1.5 kg/s, the severity of bubble splitting increases. In the study area, the irregularity of the bubble clusters results in a more chaotic flow field, leading to greater speed and displacement of the particles. Increasing the number of bubbles entering at one time and their initial speed enhances the impact of the bubble clusters on the solid particles. When the number of bubbles entering at one time is 5, 10, 15, and 20 respectively, the maximum movement speed of the particles increases by 6.9%, 8.1%, and 9.0%. When the initial speed of the bubble entering is 0, 0.1, 0.2, and 0.3 m/s respectively, the maximum movement speed of the particles increases by 6.4%, 3.0%, and 8.8%.

Pharmaceutical aerosol transport in airways: A combined machine learning (ML) and discrete element model (DEM) approach

The continuum and discrete phase interaction could significantly affect the inhaled particle's transport behaviour. The accurate analysis of continuum and discrete phase interaction needs computational fluid dynamics (CFD) and Discrete Element Method (DEM) simulation, which is computationally expensive. Therefore, this study aims to develop a novel machine learning (ML) prediction model from CFD-DEM data to predict pharmaceutical aerosol transport in airways accurately. This study uses the CFD model for the continuum and DEM for the discrete phases. A soft sphere approach was used to calculate the overlap of the colliding particles. Proper validation was performed to ensure the accuracy of the present model. The CFD-DEM model analysed the particle transport in an idealised and realistic airway model, and different methods were used to analyse the transport behaviour. As the flow rate increased from 15 to 60 lpm, the deposition efficiency (DE) significantly improved due to particle interaction, rising from 20 % to 42 % without interaction and from 50 % to a remarkable 76 % with interaction, demonstrating the critical role of particle interaction in enhancing DE across varying flow rates. During the particle-particle interaction, a stagnation point and a high-pressure zone were observed at the airway model's carinal angle. Finally, a ML prediction model is developed from CFD-DEM data, which accurately predicts the pharmaceutical aerosol deposition in airways. The ML prediction model predicts the deposition pattern for different flow rates and particle sizes without CFD-DEM simulations. The present findings and more case-specific investigation would advance the knowledge of aerosol transport in airways and benefit more efficient targeted drug delivery devices.

Efficient Dynamic Phase Splitting Driven by Centrifugal Force for CO2 Capture from Flue Gas using Biphasic Solvents.

Carbon dioxide (CO2) chemisorption using biphasic solvents has been regarded as a promising approach, but challenges remain in achieving efficient dynamic phase-splitting during practical implementation. To address this, the centrifugal force was innovatively adopted to enhance the coalescence and separation of immiscible fine droplets within the biphasic solvent. The comprehensive evaluation demonstrates that centrifugal phase-splitting shows outstanding separation efficiency (>95%) and excellent applicability for various solvents. Correlation analysis reveals a strong relationship between the rich phase's viscosity, lean phase's residual CO2, and the phase separation efficiency. The time-profile behavior of immiscible droplets, observed through microscope images of phase-splitting, enables the estimation of the growth and coalescence rates of the discrete phase. Industrial-scale process simulation for technical and economic analysis confirms that the total capture cost ($ 42.5/t CO2) can be reduced by ∼22% with the use of biphasic solvents and a centrifugal separator compared to conventional methods. This study introduces a fresh perspective on polarity-induced cluster generation and coagulation-induced separation, offering an effective solution to address the challenges associated with dynamic phase-splitting in biphasic solvents during practical applications.

Distributed Joint Beamforming for RIS-assisted Cell-Free MIMO with Discrete Phase Shifts

Abstract Both reconfiurable intelligent surface (RIS) and cell-free multiple-input multiple-output (CF-MIMO) system are holding promise to become the predominant research direction in 6G networks. This paper studies the problem of weighted sum-rate maximization(WSR) in RIS-assisted CF-MIMO networks with discrete phase shifts. We utilize alternating optimization (AO) to iteratively calculate active and passive beamforming. At access points (APs) side, we employ a distributed algorithm to design the active beamforming, leveraging information interact among APs without centralized designing at central processing unit(CPU). Facing the constraint of discrete phase shift in RIS, we adopt semidefinite relaxation(SDR) projection and proximal gradient descent(PGD) to design the passive beamforming respectively. Simulation results indicate that our proposed algorithms achieve performance comparable to the distributed framework with continuous phase shift while reducing the computational time.

Numerical investigation and passive control of dust pollution on a minivan

A dynamic model using a discrete phase approach was developed to study dust pollution on a minivan's side and rear surfaces. Numerical simulations, validated by road tests, analyzed dust concentration and distribution. A significant factor in sidewall dust pollution is the pressure difference inside and outside the wheel cavity, particularly behind the wheel cavity, which affects about 40% of the sidewall. Large trailing vortices at the rear create a low-pressure zone, leading to rear dust pollution characterized by low concentration, large area, and dispersed regions. Aerodynamic devices were proposed to mitigate pollution. Simulations showed that side attachments, such as wheel deflectors, wheel cavity baffle, and mudguards, reduce aerodynamic drag and sidewall dust pollution, with wheel cavity baffles reducing the affected area by about 48.98%. Rear attachments, like diffusers and roof deflector, minimize rear dust pollution, with roof deflector reducing the area by approximately 87.24%. These findings highlight the effectiveness of aerodynamic modifications in controlling dust pollution on a minivan.

Finite key analysis for discrete phase randomized BB84 protocol

Finite key analysis for discrete phase randomized BB84 protocol

Modeling Dense Particle Flow in Multistage and Obstructed Flow Receivers Using High Fidelity Simulations

Particles are a leading contender for next-generation, concentrating solar power technologies, and the design of the particle receiver is critical to minimize the levelized cost of electricity. Falling particle receivers (FPRs) are a viable receiver concept, but many new designs feature complex particle obstructions that include dense discrete phase flows. This creates additional challenges for modeling as particle-to-particle interactions (i.e., collisions) and particle drag become more complex. To improve upon existing modeling strategies, a CFD-DEM simulation capability was created by coupling two independent codes: Sierra/Fuego and LAMMPS. A suitable receiver model was then defined using a traditional continuum-based model for the air and a granular model for the particle curtain. A sensitivity study was executed using this model to determine the relevance of different granular model inputs on important quantities of interest in obstructed flow FPRs: the particle velocity and curtain opacity. The study showed that the granular model inputs had little effect on the particle velocity magnitude and curtain opacity after an obstruction.

Effects of delivery tube configuration regarding the gas atomization for preparing Fe-based amorphous powders: Numerical and experimental investigation

The volume of fluid (VOF) model and the discrete phase model (DPM) were adopted for primary and secondary atomization processes, respectively. The effects of the inlet-limited delivery tube geometry on the flow field, melt breakup and particle cooling were then investigated. The results show that under the delivery tube extrusion length of 5 mm, the suction effect and the breakup efficiency can be improved, and the risk of freeze-off can be inhibited. With the decrease of the delivery tube diameter from 2.5 to 1.5 mm, the calculated median diameter is decreased by more than half and the average cooling rate is more than doubled. The industrial trial results under different delivery tube diameters match the simulation results, and the stable casting of melt with low flow rate can be realized by adopting the inlet-limited delivery tube. When the delivery tube diameter is 1.5 mm, the amorphous powder has a median diameter of 38.9 μm and optimal soft magnetic properties with saturation magnetization of 135.0 emu·g−1 and coercivity of 0.26 Oe.

Mechanistic study and structural optimization for the improvement of flow field in cyclone annular space with bypass flow

The inefficiency of cyclone separation for fine particulate matter is attributed to the presence of longitudinal circulating flow and short-circuit flow in the annular space. To enhance cyclone performance, a novel cyclone design called enhanced cyclone with split flow (ECSF) has been developed, which effectively suppresses circulating flow, short-circuit flow, and eccentric circulation through bypass flow and underflow. The mechanism of bypass flow on improving the annular space’s flow field is investigated using the Reynolds stress model and discrete phase model, along with an examination of the impact of annular space height. Simulation results demonstrate that bypass flow can directly counteract vertical circulation in the annular space by creating a gas partition near the vortex finder inlet to block short-circuiting. This suppression effect on both vertical circulation and short-circuiting increases with higher bypass flow ratios. Furthermore, while the presence of an annular space limits ECSF performance optimization, its elimination simplifies structure by removing the vortex finder while maximizing separation efficiency. When no annular space exists (height = 0 mm), ECSF achieves highest separation efficiencies for 10 μm and 2.5 μm particles at approximately 96 % and 83 %, respectively; energy consumption is also minimized at only 0.94 kPa. These findings lay a foundation for future application research on ECSF.

Experimental and CFD studies on collection efficiency of separator with arc settlers of fluidized bed catalytic reactor

Separation of catalyst dust from gas in a fluidized bed reactor is an important process. A new solid-gas separator with arc settlers was developed, in which a stable wave flow pattern of the dusty gas flow is formed. The model was based on the RANS approach using the Reynolds Stress Model for the turbulence closure and the Discrete Phase Model. Validating the simulation results with the test data showed good convergence, no more than 6% in the pressure drop and less than 15.5% in collection efficiency at different inlet gas velocities. The CFD study revealed that with a dusty gas inlet velocity of no more than 1 m/s and a catalyst particle larger than 20 μm, efficiency close to 100% is achieved with a pressure drop of less than 60 Pa. Maximum efficiency is achieved when the number of rows of the arc settlers with 40 mm diameter is 8.