Computational Fluid Dynamics Model Research Articles

Image-guided patient-specific prediction of interstitial fluid flow and drug transport in solid tumors.

Tumor fluid dynamics and drug delivery simulations in solid tumors are highly relevant topics in clinical oncology. The current study introduces a novel method combining computational fluid dynamics (CFD) modeling, quantitative magnetic resonance imaging (MRI; including dynamic contrast-enhanced (DCE) MRI and diffusion-weighted (DW) MRI), and a novel ex-vivo protocol to generate patient-specific models of solid tumors in four patients with peritoneal metastases. DCE-MRI data were analyzed using the extended Tofts model to estimate the spatial distribution of tumor capillary permeability using the Ktrans parameter. DW-MRI data analysis provided a 3D representation of drug diffusivity, and DW-MRI coupled to an ex-vivo measurement protocol informed the spatial heterogeneity of the hydraulic conductivity of tumor tissue. The patient-specific data were subsequently incorporated into a computational fluid dynamics (CFD) model to simulate individualized tumor perfusion and drug transport maps. The results on interstitial fluid flow demonstrated noticeable heterogeneity of interstitial fluid pressure and velocity within the tumor, along with heterogeneous drug penetration profiles among different tumors, even with a similar drug administration regimen.

Simulation of the fluid flow pattern and property estimation for bio-diesel plant design

The fluid flow pattern that occurs in the bio-diesel production process is related to viscosity, flow velocity, and pressure. Fluid flow is a paramount cause of failure in pipes in several industries. The heat transfer cause across pipes needs to be analyzed to avoid failure during operation. The simulation and visualization of fluid flow in the plant pipes were developed for the pressure drop along with the length of the pipe. Flow patterns was analyzed using a Computational Fluid Dynamics model approach (CFD). The CFD within the ANSYS environment has three important stages, namely pre-processing, finding solutions, and post-processing. Mesh was generated and the material properties were assigned. The boundary conditions were stipulated, and the process analyzed to ensure convergence of the solution in a stable state. High density of the blend was observed for 40% bio-diesel blend and low density at 5% bio-diesel blend. The results of the correlation analysis shows that density is directly proportional to bio-diesel content. The density-composition depict a uniform increasing density value with percentage bio-diesel mixture content. The viscosity slightly increases with bio-diesel content. There is a clear trend of viscosity increasing proportional to bio-diesel content. The simulation ensures that the parameters for the design and fabrication of the bio-diesel reactor as obtained from the simulation results is optimal.

Duodenogastric Reflux in Health and Disease: Insights from a Computational Fluid Dynamics Model of the Stomach.

The stomach is responsible for physically and chemically processing the ingested meal before controlled emptying into the duodenum through the pyloric sphincter. An incompetent pylorus allows reflux from the duodenum back into the stomach, and if the amount of reflux is large enough, it could alter the low pH environment of the stomach and erode the mucosal lining of the lumen. In some cases, the regurgitated contents can also reach the esophagus leading to additional complications. In this work, "StomachSim", an in-silico model of the fluid dynamics of the stomach, is used to study the mechanism of duodenogastric reflux. The effects of variations in food properties and motility disorders on reflux are investigated. The simulations show that the primary driver of reflux is the relaxation of the antrum after a stomach contraction terminates near the pylorus. The region of the stomach walls exposed to the regurgitated contents depends significantly on the density of the stomach contents. For stomach contents of higher viscosity, the increased pressure required to maintain gastric emptying reduces the amount of duodenogastric reflux. Concomitant stomach motility disorders that weaken the relaxation of the walls also affect the amount of reflux. The study illustrates the utility of in-silico models in analyzing the factors at play in gastrointestinal diseases.

Experimental validation of a simplified CFD model for a PCM-water finned heat exchanger

Abstract The most widely used numerical models in the scientific literature for simulating heat exchangers with phase change materials (PCMs) and water as the heat transfer fluid, are based on computational fluid dynamics (CFD) techniques, with the modelling of phase change being the key issue. The consideration of phase change effect, as well as the resolution of the movement of the PCM in the liquid state, make CFD models computationally very expensive. However, various published experiments indicate that during the heat discharge process, the dominant heat transfer mechanism is conduction in the solidified PCM around the finned tube. For this reason, this article presents a simplified CFD model, where convective flow of the PCM is neglected during the discharge process. The model was validated experimentally, and to achieve this validation process, an experimental prototype of a one-meter-long axially finned heat exchanger with four fins was built. Inlet and outlet water temperatures were continuously recorded, along with temperatures at various points inside the PCM, under four different water flow rates. The proposed numerical model was able to predict the outlet water temperature with an error smaller than 1°C in all cases, and to capture the observed trend in temperature inside the PCM.

COMPUTATIONAL FLUID DYNAMIC MODEL TO SIMULATE THE DISPERSION OF ATMOSPHERIC NH3 GENERATED BY A COWSTABLE IN LA LAGUNA, MEXICO

Stalls are one of the main causes of ammonia (NH3) buildup. These harmful gases have increased their concentration in the air in recent years. However, there are few studies on their dispersion to the atmosphere, since they constitute a passive polluting system in livestock areas. Therefore, the objective of this research was to evaluate the distribution of NH3 pollutants concerning temperature, humidity, and airflow in a stable, through a computational fluid dynamics model and its analysis using the K2 algorithm. The model consisted of simulated 20 production units with similar environmental conditions and took the initial values​​from data obtained from a nearby weather station in a region characterized by semi-arid climatic conditions. The highest concentration of NH3 was obtained under a wind velocity of 0 ms-1 due to the stagnation of the pollutant. The results indicated that levels of only 0.48 ms-1 reduce the concentration of NH3 by 13 %. The results were analyzed using the K2 algorithm to obtain the relationship and inferences between NH3 emissions, air flow velocity, ambient temperature, and humidity. The analysis of the CFD approach using the K2 algorithm concluded that temperature (85 %) and humidity (98 %) are the main variables that influence the pollution produced by the distribution of NH3 to the environment derived from livestock activity.

Three-dimensional CFD simulation of co-gasification of biomass and plastic wastes (SRF) in a bubbling fluidized bed with detailed kinetic chemical model

In this study, a three-dimensional computational fluid dynamics (CFD) model using multiphase particle-in-cell (MP-PIC) method with large eddy simulation (LES) was developed to investigate the characteristics of the co-gasification of densified wood pellets (WP) and rice husk pellets (RHP) with SRF in a bubbling fluidized bed reactor. ER reduction from 0.30 to 0.10 resulted in a decrease in specific gas yield per total feed from 1.20 g/gtotal to 0.96 g/gtotal and from 1.20 g/gtotal to 0.67 g/gtotal during SRF/WP and SRF/RHP co-gasification, respectively. Reducing ER during SRF/WP co-gasification allows to increase C2–C3 HCs yield reaching 0.33 g/gsrf (0.15 g/gtotal) at ER = 0.15, 0.556 kg/h SRF, and 0.693 kg/h WP. Carbon conversion efficiency (CCE) and cold gas efficiency (CGE) at the same conditions reduced to 83% and 74%, respectively. Co-gasification of 0.667 kg/h SRF and 2.040 kg/h RHP allowed to reach 0.28 g/gsrf (0.07 g/gtotal) C2–C3 HCs yield, but drastically reducing CCE and CGE to 71% and 46%, respectively. SRF/WP co-gasification is suggested for low cost C2–C3 HCs recovery from SRF with coproduction of syngas retaining 48% to 57% of initial LHV, meaning that SRF/RHP co-gasification is more suitable for syngas production.

Spill-free Robotic Arm Based on Pendulum Model

This paper investigates the application of a pendulum model in designing and simulating a 5-DOF robotic system that transports an open-top container filled with liquid free of any spill. In this work, the robot consists of a 3-DOF robotic arm for positioning and a 2-DOF end-effector for adjusting the containers orientation to prevent spillage. The system is implemented using both Matlab Simulink and Simscape environment. In this hybrid setup, Simscape handles the robots kinematic modeling, while Simulink is used for controlling the end-effectors orientation with a PID controller. Under the pendulum model, the gripper, the open-top container and the liquid move as one mass along the pendulum trajectory, so that no liquid is spilled out during the movement. Results indicate trajectory tracking accuracy. This approach avoids the need for complicated computational fluid dynamics model and underscores the advantages of autonomous mobile robots in achieving reliable performance in spill-free liquid handling, a task difficult to achieve for human beings.

Computational Evaluation of Improved HIPEC Drug Delivery Kinetics via Bevacizumab-Induced Vascular Normalization

Background: Oxaliplatin-based hyperthermic intraperitoneal chemotherapy (HIPEC) using the original 30 min protocol has shown limited benefits in patients with peritoneal metastasis of colorectal cancer (PMCRC), likely due to the short duration, which limits drug penetration into tumor nodules. Bevacizumab, an antiangiogenic antibody that modifies the tumor microenvironment, may improve drug delivery during HIPEC. This in silico study evaluates the availability of oxaliplatin within tumor nodules when HIPEC is performed after bevacizumab treatment. Methods: Using a computational fluid dynamics (CFD) model of HIPEC, the temperature and oxaliplatin distribution within the rat abdomen were calculated, followed by a model of drug transport within tumor nodules located at various sites in the peritoneum. The vascular normalization effect of the bevacizumab treatment was incorporated by adjusting the biophysical parameters of the tumor nodules. The effective penetration depth values, including the thermal enhancement ratio of cytotoxicity, were then compared between HIPEC alone and HIPEC combined with the bevacizumab treatment. Results: After bevacizumab treatments at doses of 0.5 mg/kg and 5 mg/kg, the oxaliplatin availability increased by up to 20% and 45% when HIPEC was performed during the vascular normalization phase, with the penetration depth increasing by 1.5-fold and 2.3-fold, respectively. Tumors with lower collagen densities and larger vascular pore sizes showed higher oxaliplatin enhancement after the combined treatment. Bevacizumab also enabled a reduction in the oxaliplatin dose (up to half at 5 mg/kg bevacizumab) while maintaining effective drug levels in the tumor nodules, potentially reducing systemic toxicity. Conclusions: These findings suggest that administering oxaliplatin-based HIPEC during bevacizumab-induced vascular normalization could significantly improve drug penetration and enhance treatment efficacy.

Computational Fluid Dynamic Modeling of Pack-Level Battery Thermal Management Systems in Electric Vehicles

In electric vehicles (EVs), the batteries are arranged in the battery pack (BP), which has a small layout space and difficulty in dissipating heat. Therefore, in EVs, the battery thermal management systems (BTMSs) are critical to managing heat to ensure safety and performance, particularly under higher operating temperatures and longer discharge conditions. To solve this problem, in this article, the thermal analysis models of a 3-battery-cell BP were created, including scenarios (1) natural air cooling without a BTMS; (2) natural air cooling with water cooling hybrid BTMS; and (3) forced air cooling plus water cooling composite BTMS. The thermal performances of the pack-level BPs were simulated and analyzed based on computational fluid dynamics (CFD). A variety of boundary conditions and working parameters, such as ambient temperature, inlet coolant flow rate and initial temperature, discharge rate, air flow rate, and initial temperature, were considered. The results show that without a BTMS (Scenario 1), the maximum temperature in the BP rises rapidly and continuously to reach 63.8 °C, much higher than the upper bound of the recommended operating temperature range (ROTR between +20 °C to +35 °C) under the extreme discharge rate of 3 C and even if the discharge rate is 2 C. With a hybrid BTMS (Scenario 2), the maximum temperature in BP rises to about 38.7 °C, slightly above the upper bound of the ROTR. Lowering the coolant (water) initial temperature can effectively lower the temperature up to 5.7 °C in BP, but the water flow rate cannot since the turbulence model. While with a composite BTMS (Scenario 3), the temperature can be further lowered up to 1.5 °C under the extreme discharge rate of 3C, just reaching the upper bound of the ROTR. In addition, lowering the initial coolant temperature or air temperature can effectively decrease the temperatures up to 5.1 and 1.0 °C, respectively, in BP, but the coolant flow rate (due to the turbulence model) and the air flow rate cannot. Finally, the thermal performances of the different battery cells in the BP with different cooling systems and at the different positions of the BP were compared and analyzed. The present work may contribute to the design of BTMSs in the EV industry.

A multi-modal computational fluid dynamics model of left atrial fibrillation haemodynamics validated with 4D flow MRI.

Atrial fibrillation (AF) is characterized by rapid and irregular contraction of the left atrium (LA). Impacting LA haemodynamics, this increases the risk of thrombi development and stroke. Flow conditions preceding stroke in these patients are not well defined, partly due the limited resolution of 4D flow magnetic resonance imaging (MRI). In this study, we combine a high-resolution computed tomography (CT) LA reconstruction with motion and pulmonary inflows from 4D flow MRI to create a novel multimodal computational fluid dynamics (CFD) model, applying it to five AF patients imaged in sinus rhythm (24 ± 39 days between acquisitions). The dynamic model was compared with a rigid wall equivalent and the main flow structures were validated with 4D flow MRI. Point-by-point absolute differences between the velocity fields showed moderate differences given the sensitivity to registration. The rigid wall model significantly underestimated LA time-averaged wall shear stress (TAWSS) (p = 0.02) and oscillatory shear index (OSI) (p = 0.02) compared to the morphing model. Similarly, in the left atrial appendage (LAA), TAWSS (p = 0.003) and OSI (p < 0.001) were further underestimated. The morphing model yielded a more accurate mitral valve waveform and showed low TAWSS and high OSI in the LAA, both associated with thrombus formation. We also observed a positive correlation between indexed LA volume and endothelial cell activation potential (ECAP) (R2 = 0.83), as well as LAA volume and LAA OSI (R2 = 0.70). This work demonstrates the importance of LA motion in modelling LAA flow. Assessed in larger cohorts, LAA haemodynamic analysis may be beneficial to refine stroke risk assessment for AF.

Development of CPAP Overlay Interfaces for Efficient Administration of Aerosol Surfactant Therapy to Preterm Infants

The administration of surfactant aerosol therapy to preterm infants receiving continuous positive airway pressure (CPAP) respiratory support is highly challenging due to small flow passages, relatively high ventilation flow rates, rapid breathing and small inhalation volumes. To overcome these challenges, the objective of this study was to implement a validated computational fluid dynamics (CFD) model and develop an overlay nasal prong interface design for use with CPAP respiratory support that enables high efficiency powder aerosol delivery to the lungs of preterm infants when needed (i.e., on-demand) and can remain in place without increasing the work of breathing compared with a baseline CPAP interface. Realistic in vitro experiments were first conducted to generate baseline validation data, and then the CFD model, once validated, was used to explore key design parameters across a range of preterm infant nose-throat geometries and aerosol delivery conditions. The most important factors for efficient aerosol delivery were shown to be (i) maintaining the aerosol delivery flow rate below the tracheal flow rate (to minimize CPAP line loss) and (ii) concentrating the aerosol within the first portion of the inhalation waveform. An optimized design was shown to deliver approximately 37–60% of the nominal dose through the system and to the lungs with low intersubject variability (1050–2200 g infants) across two modes of device actuation (automated and manual) with room for further improvement. Ergonomic curvatures and streamlining of the prong geometries were also found to reduce work of breathing and flow resistance compared with a commercial alternative.Graphical

Numerical analysis on heat transfer enhancement of Al2O3 and CuO-water nanofluids in annular curved tubes

The present investigation presents numerically the thermo-hydraulic performance of annular curved tubes in the turbulent flow region. The three-dimensional (3D) computational fluid dynamic (CFD) model was developed by using a commercial ANSYS 14.5 package to get additional insights on the thermo-hydraulic performance on a level of detail that is not always available in experiment results. The turbulent k-ε realize model was employed to examine the effect of Al2O3-water and CuO-water nanofluids on the heat transfer and fluid flow characteristics at different key design parameters. Three coil geometry shapes (including helical, spiral, and conical), five annular cross-section shapes (including circular, elliptical, square, rectangular, and triangular), and three cross-section areas were also investigated in this study. The numerical simulations were carried out at Reynolds numbers of 4700 to 26,700 and nanofluid volume concentrations, φ of 1%, 3%, and 5%, with constant wall temperature (CWT) heat transfer boundary conditions. The result showed that the addition of Al2O3 (45 nm) and CuO (29 nm) nanoparticles to water improves the heat transfer coefficient by 48.8%, 25.7%, and 8.4% and 37.1%, 20%, and 8.7%, respectively, at φ of 5%, 3%, and 1%, while the penalty of pressure drop is approximately negligible. The heat transfer rate per unit pumping power for helical design achieved 21.6% and 5.34% higher than conical and spiral designs, respectively, for the same curvature ratio, cross-section area, and coil length. Also, the circular shape achieved a higher heat transfer enhancement than elliptical, square, rectangular, and triangular shapes by 4%, 14.6%, 17.8%, and 30.1%, respectively. The maximum thermo-hydraulic performance index reached 1.68 and 1.58 for both Al2O3-water and CuO-water nanofluids, respectively, at φ of 5%.

Convective forces contribute to post‐traumatic degeneration after spinal cord injury

AbstractSpinal cord injury (SCI) initiates a complex cascade of chemical and biophysical phenomena that result in tissue swelling, progressive neural degeneration, and formation of a fluid‐filled cavity. Previous studies show fluid pressure above the spinal cord (supraspinal) is elevated for at least 3 days after injury and contributes to a phase of damage called secondary injury. Currently, it is unknown how fluid forces within the spinal cord itself (interstitial) are affected by SCI and if they contribute to secondary injury. We find spinal interstitial pressure increases from −3 mmHg in the naive cord to a peak of 13 mmHg at 3 days post‐injury (DPI) but relatively normalizes to 2 mmHg by 7 DPI. A computational fluid dynamics model predicts interstitial flow velocities up to 0.9 μm/s at 3 DPI, returning to near baseline by 7 DPI. By quantifying vascular leakage of Evans Blue dye after a cervical hemi‐contusion in rats, we confirm an increase in dye infiltration at 3 DPI compared to 7 DPI, suggestive of higher fluid velocities at the time of peak fluid pressure. In vivo expression of the apoptosis marker caspase‐3 is strongly correlated with regions of interstitial flow at 3 DPI, and exogenously enhancing interstitial flow exacerbates tissue damage. In vitro, we show overnight exposure of neuronal cells to low pathological shear stress (0.1 dynes/cm2) significantly reduces cell count and neurite length. Collectively, these results indicate that interstitial fluid flow and shear stress may play a detrimental role in post‐traumatic neural degeneration.

FLUID FLOW CHARACTERISTICS IN A SHELL AND TUBE HEAT EXCHANGER WITH SWIRL BAFFLES

This paper presents a numerical investigation into the fluid flow and heat transfer characteristics of a shell and tube heat exchanger (STHeX) equipped with baffles that induces swirl flow. A Computational Fluid Dynamics (CFD) model was created to simulate the STHeX behavior, and its accuracy was confirmed by comparing it to the Bell-Delaware method results. The two sets of calculations exhibited good agreement, validating the CFD model. The velocity component of the fluid flow was analyzed both qualitatively and quantitatively. The flow patterns of eddies on the STHeX were carefully examined and their correlation with thermal performance was investigated. This study demonstrates that the swirl flow baffle geometry leads to a more turbulent flow pattern, resulting in an increase in the overall heat transfer coefficient. The findings indicate that the swirl flow baffle enhances heat transfer performance and reduces pressure drop in comparison to a conventional STHeX.

A Review of Modeling, Simulation, and Process Qualification of Additively Manufactured Metal Components via the Laser Powder Bed Fusion Method

Metal additive manufacturing (AM) has grown in recent years to supplement or even replace traditional fabrication methods. Specifically, the laser powder bed fusion (LPBF) process has been used to manufacture components in support of sustainment issues, where obsolete components are hard to procure. While LPBF can be used to solve these issues, much work is still required to fully understand the metal AM technology to determine its usefulness as a reliable manufacturing process. Due to the complex physical mechanisms involved in the multiscale problem of LPBF, repeatability is often difficult to achieve and consequently makes meeting qualification requirements challenging. The purpose of this work is to provide a review of the physics of metal AM at the melt pool and part scales, thermomechanical simulation methods, as well as the available commercial software used for finite element analysis and computational fluid dynamics modeling. In addition, metal AM process qualification frameworks are briefly discussed in the context of the computational basis established in this work.

Numerical analysis of transonic flow over the FFA-W3-211 wind turbine tip airfoil

Abstract. Modern wind turbines are the largest rotating machines ever built, with blade lengths exceeding 100 m. Previous studies demonstrated how the flow around the tip airfoils of such large machines reaches local flow Mach numbers (Ma), at which the incompressibility assumption might be violated, and, even in normal operating conditions, local supersonic flow could appear. In the present study, a numerical analysis of the FFA-W3-211 wind turbine tip airfoil is performed. The results are obtained by means of the application of numerical tools: (1) XFOIL with the Prandtl–Glauert compressible correction and (2) computational fluid dynamic (CFD) simulations, where an unsteady Reynolds-averaged Navier–Stokes (URANS) model is used. A preliminary validation of the latter CFD model is performed to demonstrate that the URANS approach is a viable method for predicting the aerodynamic performances in compressible and transonic flow that provides additional and more reliable information compared to the classical compressibility corrections. From this study, three key findings can be highlighted. Primarily, the main transonic features of the FFA-W3-211 wind turbine tip airfoil have been assessed, selecting specific test cases of particular industrial interest. Then, the threshold between subsonic and supersonic flow is provided, considering also an increase of the Reynolds number (Re) from a characteristic value used in the wind tunnel experiments to the one realistic for large rotors. A strong dependence on this quantity is observed, revealing that, for the same Mach number, also the Reynolds number plays a crucial role in promoting the occurrence of transonic flow. Finally, the possible presence or absence of shock waves was investigated. The results indicate that the appearance of transonic flow is a necessary but not a sufficient condition to lead to shock formation.

Computational Fluid Dynamics (CFD) Modeling of Material Transport through Triply Periodic Minimal Surface (TPMS) Scaffolds for Bone Tissue Engineering.

Cell-laden, scaffold-based tissue engineering methods have been successfully utilized for the treatment of bone fractures. In such methods, the rate of scaffold biodegradation, transport of nutrients, and removal of cell metabolic wastes are critical fluid-dynamics factors, affecting tissue regeneration. Therefore, there is a critical need to identify the underlying material transport mechanisms associated with stem cell-driven, scaffold-based bone tissue regeneration. The objective of the work is to establish computational fluid dynamics (CFD) models to identify the consequential mechanisms behind internal and external material transport through/over porous bone scaffolds designed based on the principles of triply periodic minimal surfaces (TPMS). In this study, advanced CFD models were established based on ten TPMS designs for analyzing (i) single-unit internal flow, (ii) single-unit external flow, and (iii) cubic, full-scaffold external flow. The main fluid characteristics influential in bone regeneration, including flow velocity, pressure, and wall shear stress (WSS), were analyzed to assess material transport internally through and externally over the TPMS designs. Schwarz Primitive (P) appeared to have the lowest level of flow pressure and WSS (desirable for development of bone tissues). An analysis of streamline velocity exhibited an increase in velocity togther with a depiction of turbulent motion along the curved surfaces of the TPMS designs. Besides, pressure buildup was observed within the inner channels of almost all the TPMS designs. Overall, the outcomes of this study pave the way for optimal design and fabrication of bone-like tissues with desirable medical properties.

A Fuel Cell Power Supply System Equipped with Artificial Gill Membranes for Underwater Applications.

This work proposes a fuel cell power supply system for underwater applications (e.g., autonomous underwater vehicles), where artificial gills, based on a polymer membrane,harvest the required oxygen from the ambient water. In this system, a circulating air-flow continuously supplies a proton exchange membrane fuel cell with oxygen, which is replenished using a polymer membrane. The membrane serves as the interface between the circulating air-flow and the ambient water, preventing water flux while allowing an oxygen flux across the membrane, driven by a partial oxygen pressure gradient. To demonstrate the feasibility of this concept, a prototype system was built based on guidelines derived from a mathematical model that was developed to describe the oxygen transfer process. A computational fluid dynamics model is developed and validated against the measurements from the prototype, resulting in a digital twin. The analysis indicates that the proposed power supply system has the potential to be superior to any battery-based solution currently available.

Computational Fluid Dynamics as a Digital Tool for Enhancing Safety Uptake in Advanced Manufacturing Environments Within a Safe-by-Design Strategy.

In modern manufacturing environments, pollution management is critical as exposure to harmful substances can cause serious health issues. This study presents a two-stage computational fluid dynamic (CFD) model to estimate the distribution of pollutants in indoor production spaces. In the first stage, the Reynolds-averaged Navier-Stokes (RANS) method was used to simulate airflow and temperature. In the second stage, the Lagrangian method was applied for particle tracing. The model was applied to a theoretical acrylonitrile butadiene styrene (ABS) filament 3D printing process to evaluate the factors affecting the distribution of ultrafine particles (30 nm). Key parameters such as ventilation system effects, the presence of cooling fans and the print bed, and nozzle temperatures were considered. The results show that the highest flow velocities (1.97 × 10-6 m/s to 3.38 m/s) occur near the ventilation system's inlet and outlet, accompanied by regions of high turbulent kinetic energy (0.66 m2/s2). These conditions promote dynamic airflow, facilitating particulate removal by reducing stagnant zones prone to pollutant buildup. The effect of cooling fans and thermal sources was investigated, showing limited contribution on particle removal. These findings emphasize the importance of digital twins for better worker safety and air quality in 3D printing environments.

CFD modelling and simulations of atomization-based processes for production of drug particles: A review.

Atomization-based techniques are widely used in pharmaceutical industry for production of fine drug particles due to their versatility and adaptability. Key performance measure of such techniques is their ability to provide control over critical quality attributes (CQAs) of produced drug particles. CQAs of drug particles produced via atomization critically depend on fluid dynamics of sprays; resulting mixing, heat and mass transfer; distribution of supersaturation and subsequent nucleation and growth of particles. It is essential to develop and use computational fluid dynamics (CFD) models for adequate understanding of multi-scale transport processes ranging from molecular scale mixing and particle scale processes, and from atomizer nozzle to overall spray chamber scale establishing relationships between CQAs and design and operating parameters of spray nozzle and chamber. In this work, we critically review past and current research efforts on CFD modelling of pharmaceutical atomization-based processes with an objective to provide clear assessment of the state of the art and to provide recommendations. An overview of the key atomization-based methods for producing drug particles with desired CQAs is presented. Key underlying physical processes and relevant concepts are then outlined. This discussion is related to the demands on CFD models; and state of the art is then discussed with respect to the process needs. Recommendations are provided towards higher fidelity and more efficient models of atomized multiphase flow dynamics and turbulence, drying modelling for the produced particles, and validation approaches. We conclude by highlighting a perceived need for numerical atomization studies with a pharmaceutical context; then, we deliver an outlook on current promising active control and machine learning strategies to augment the shift towards quality-by-design approaches in pharmaceutical manufacturing.