Multiscale Computational Fluid Dynamics Research Articles

Framework for integrated multi-scale computational fluid dynamics simulations in natural ventilation design

The wind flow field constitutes an important input parameter for computational fluid dynamics (CFD) simulations that are used in architectural design for the design and analysis of natural ventilation strategies. Despite indications that the wind flow field may vary between places, CFD simulations that do not adequately account for this potential variation are still commonplace. This may significantly compromise the integrity and accuracy of the CFD simulations. This study was a two-pronged investigation with the ultimate objective of contributing towards efforts aimed at improving the accuracy of the CFD simulations. Firstly, a framework for integrated meso-scale and micro-scale CFD simulations was developed. Secondly, the newly developed framework was then implemented by deploying it to study the variation of the wind flow field between a reference meteorological station, and a selected local building site. The findings confirmed the indications that the wind flow field might vary spatially. The integrated multi-scale framework that was developed as part of the study was not only able to capture the wind flow field variation, but it also provided a way to quantify it, ultimately, leading to the generation of a more accurate wind flow field characterization representative of the local conditions. Through its ability to integrate multiple spatial scales that typically influence one another, this framework can help to enhance the accuracy and integrity of the CFD simulations that are used for natural ventilation design. Practical application: The findings from this study can be particularly useful when undertaking spatially integrated CFD simulations to design and analyse natural ventilation strategies in the building design process.

Investigation of particle flow effects in slug flow crystallization using the multiscale computational fluid dynamics simulation

This article discusses the development of a new computational fluid dynamics (CFD) model, the MVP (MP-PIC coupled with VOF and PBE) method, which predicts the slug flow crystallization phenomenon. The model is capable of predicting the flow of gas–liquid-solid phases and the associated chemical and particle changes. The MVP model is validated through a comparison with an experimental study on LAM (L-asparagine monohydrate) crystallization, and the results demonstrate its ability to accurately predict the three-phase fluid flow with particle size variation. In particular, we have been able to predict the effect of slug length change on particle mixing and predict hydrodynamic factors such as the particle streamlines and the circulation number of the particle phase via case studies. Overall, the MVP model is expected to offer a new way to accurately predict slug flow crystallization and provide valuable information for the process intensification of crystallization.

In silico hemodynamical simulations show additional benefits of artery wall softening induced by antihypertensive drugs

Background and objectivesAge-related arterial stiffening increases peripheral resistance and decreases arterial distensibility, thus contributing to hypertension, an important risk factor of atherosclerosis. It causes abnormal blood flow, endothelial dysfunction, higher pulse wave velocity, and consequently elevated pressure wave amplitude. MethodsThis paper presents the influence of these changes via multiscale 3D-0D transient computational fluid dynamics simulations of blood flow in five patient-specific geometries of human carotid bifurcation using archetypal flow waveforms for young and old subjects. ResultsThe proposed model shows a significant decrease in the time-averaged wall shear stress (TAWSS) for the old archetypal flow waveform. This is in good agreement with clinical data on a straight segment of common carotid arteries available for young and old subjects. Moreover, our study showed that the decrease of area-averaged TAWSS related to the old flow waveform is much more pronounced (2.5 ÷ 4.5 times higher) at risk areas (areas showing TAWSS below its threshold value of 0.48 Pa) than in straight segments commonly considered in clinical studies. ConclusionsSince arterial stiffness can be lowered through long-term usage of any of the five basic groups of antihypertensives, possible benefits of such medical therapy could be not only lowering blood pressure and peripheral resistance but also in increasing the TAWSS and thus attenuating an important mechanism of the atherosclerotic process.

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.

Numerical simulation analysis of multi-scale computational fluid dynamics on hemodynamic parameters modulated by pulsatile working modes for the centrifugal and axial left ventricular assist devices

Continuous flow (CF) left ventricular assist devices (LVAD) operate at a constant speed mode, which could result in increased risk of adverse events due to reduced vascular pulsatility. Consequently, pump speed modulation algorithms have been proposed to augment vascular pulsatility. However, the quantitative local hemodynamic effects on the aorta when the pump is operating with speed modulation using different types of CF-LVADs are still under investigation. The computational fluid dynamics (CFD) study was conducted to quantitatively elucidate the hemodynamic effects on a clinical patient-specific aortic model under different speed patterns of CF-LVADs. Pressure distribution, wall shear stress (WSS), time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and velocity were calculated to compare their differences at constant and pulsatile speeds under centrifugal and axial LVAD support. Results showed that pulse pressure on the aorta was significantly larger under pulsatile speed mode than that under constant speed mode for both CF-LVADs, indicating enhanced aorta pulsatility, as well as the higher peak blood flow velocity on some representative slices of aorta. Pulsatile speed modulation enhanced peak WSS compared to constant speed; high TAWSS region appeared near the branch of left common carotid artery and distal aorta regardless of speed modes and CF-LVADs but these regions also had low OSI; RRT was almost the same for all the cases. This study may provide a basis for the scientific and reasonable selection of the pulsatile speed patterns of CF-LVADs for treating heart failure patients.

Diode effects on street canyon ventilation in valley city: Temperature inversion and calm geostrophic wind

In urban areas, especially in valleys, challenges from heat and pollution are common. The situation worsens due to temperature inversions, where warm air traps pollutants. A new study employed multi-scale computational fluid dynamics (CFD) to assess ventilation in valley cities, specifically during temperature inversions and calm winds. Parameters like air change rate (ACH), local mean age of air (LMAA), and purging flow rate (PFR) were used to gauge street canyon ventilation efficiency. Factors such as atmospheric stability, city-slope positioning, and surface materials are altered to analyze impacts on urban heat island (UHI) intensity and air quality.Results indicated that katabatic winds had varied effects on pollution in different city regions, influenced by atmospheric conditions. Higher temperature lapse rates led to enhanced pollutant removal near slopes due to vortex interactions, but distant regions experienced thicker inversion layers, limiting pollutant dispersion. Conversely, anabatic winds improved ventilation with distance. Under inversion conditions, slope-city distance and surface materials played roles.For katabatic winds, city positioning significantly reduced UHI intensity, lowering LMAA by around 440s. Anabatic winds' UHI impacts ranked as atmospheric conditions, city location, and surface materials. A neutral atmosphere reduced UHI by 4.5K, but increased distance between city and slopes strengthened UHI by 4.04K. Ventilation efficiency was mainly tied to atmospheric conditions, while city location impacted pollution mitigation.This research aids in understanding air quality and airflow patterns during extreme weather events, aiding urban canyon design in valleys, especially with recurring heatwaves.

Interactive steering on in situ particle-based volume rendering framework

The development of supercomputers and multi-scale computational fluid dynamics (CFD) models based on adaptive mesh refinement (AMR) enabled fast, large-scale, and high fidelity CFD simulations. Interactive in situ steering is an effective tool for debugging, searching for optimal solutions, and analyzing inverse problems in such CFD simulations. We propose an interactive in situ steering framework for large-scale CFD simulations on GPU supercomputers. This framework employs in situ particle-based volume rendering (PBVR), in situ data sampling, and a file-based control that enables interactive and asynchronous communication of steering parameters, compressed visualization particle data, and sampled monitoring data between supercomputers and user PCs. The parallelized PBVR is processed on the host CPU to avoid interference with CFD simulations on the GPU. We apply the proposed framework to a real-time plume dispersion analysis code CityLBM, which computes the lattice Boltzmann method on the block AMR grid using GPU supercomputers. In the numerical experiment, we address an inverse problem to find a pollutant source from the observation data at monitoring points and demonstrate the effectiveness of the human-in-the-loop approach via the in situ steering framework.Graphical abstract

Multiscale Modeling of Radio Frequency Reactor Coupled Catalyst Heating for Ethylene Production

Ethylene is the petrochemical compound with the highest production worldwide. Whether reactors are heated by direct fired heating or indirect heating via steam, manufacturers rely on economies of scale to overcome inherent thermodynamic inefficiencies while burning fossil fuels. New approaches to supply energy to chemical reactor systems can reduce energy waste created by traditional techniques while enabling large scale facilities to use other sources of raw materials and energy. Electromagnetic (EM) induction heating is one potential solution for providing energy efficiently to reactor systems. By taking advantage of the nature of radio frequency (RF) waves, heterogeneous-catalyst can be precisely targeted for heating inside the reactors. Site-selective heating can significantly reduce the energy requirements of the process by providing heat at reaction sites and reducing unnecessary heat transfer elsewhere. Other advantages to an EM enhanced system include rapid volumetric heating, broader turn-down capacity, and reduced process footprint.The purpose of this work is to establish a multiscale computational fluid dynamics (CFD) model that can be used to emulate the proposed process mechanics at the macroscale and microscale. At the macroscale, coil geometry (coil diameter, gap between coils, distance between coil and susceptors) is investigated to elucidate coil design and effects on heating rates. In the microscale, the oxidative (CO2) dehydrogenation (ODH) of ethane is explored using different catalysts and possible catalyst/susceptor configurations with heat supplied by an EM susceptor. This multiscale method can also be applied to electrochemical systems.

Multiscale CFD Simulation of Multiphase Erosion Process in a Connecting Pipe of Industrial Polycrystalline Silicon Unit

Severe erosion phenomena often occur in industrial polycrystalline silicon units, leading to hydrogen leakage accidents and affecting long-term operation. It is favorable to use a computational fluid dynamics (CFD) simulation with the dense discrete phase model (DDPM) and the sub-grid energy-minimization multi-scale (EMMS) drag model to improve the prediction accuracy of complex multiphase erosion phenomena in a connecting pipe of an industrial polycrystalline silicon unit. Furthermore, the effect of droplet the specularity coefficient on boundary conditions is thoroughly considered. The predicted erosion behaviors are consistent with industrial data. The effects of operations parameters were discussed with three-dimensional CFD simulation, including droplet size and hydrogen volume fraction on erosion behaviors. The results indicated that the non-uniform multiphase erosion flow behavior near the wall can be simulated accurately with the EMMS drag model in a coarse mesh. A suitable droplet specularity coefficient such as 0.5 can also improve the accuracy of erosion position. Small liquid droplets, such as those of 30 μm size, will follow the gas phase better and have a lower erosion rate. The inertia effect of large droplets, such as those of 150 μm size, plays a dominant role, resulting in obvious erosion on the elbow walls. The erosion range and thinning rate enlarge with the increase in hydrogen volume fraction. A few silicon solid particles, such as 0.01% volume fraction, change local flow behaviors and probably cause the variation of local erosion positions. The process of erosion deformation first circumferentially extended and then accelerated at the local center position deeper.

Multiscale CFD modelling for conformal atomic layer deposition in high aspect ratio nanostructures

The high-quality and conformal thin film is of great importance to performances of functional materials and devices with high aspect ratio nanostructures. Atomic layer deposition (ALD) is known for outstanding step coverage, yet the ideal coatings in high aspect ratio nanostructures requires the process optimization. In this work, we report a computationally efficient multiscale computational fluid dynamics (CFD) model for an accurate study of ALD process in high aspect ratio nanostructures. The continuum model of precursor mass transfer and surface micro-kinetics in the high aspect ratio nanostructure is coupled to the reactor scale CFD model. The dynamic distribution of the precursor in the high aspect ratio nanostructure is captured and the competition of the surface deposition with the precursor transfer has been analyzed. The complete ALD process parameters including pulse, pressure-holding and purging are studied. Increasing the gas flow rate correspondingly reduces the gas phase reaction, ensures the conformability, and shortens the process time. Pressure-holding leads to a better film conformality for the diffusion-limited ALD process, especially for precursors of low reactivity. The experiment of ALD coating in nanopores with an aspect ratio up to 100:1 agrees well with our simulation results, indicating the validity of the multiscale model. Multiscale modelling provides a manner to quantitatively study the comprehensive effects of full-scale parameters for better conformity and process efficiency.

Numerical Study of the Influence of the Geometric Parameters of a Radial Crystalizer Using a Multiscale CFD Model

This work investigates how the configuration of the geometric parameters of a radial crystallizer influences the results of the crystallization of lovastatin by antisolvent and using a multi-scale computational fluid dynamics (CFD) model. The OPENFOAM open-source software uses macro and micromixing expressions for flow, and complete energy and population equilibrium equations during nucleation and crystal growth. The model is based on the Reynolds-Averaged-Navier-Stokes (RANS) equation, along with a multi-environment probability density function (PDF) model and the spatially semi-discretized population equilibrium equation, operating a high-resolution finite volume method. The variation crystallizer construction parameters provided another crystallizer design, and analyses demonstrated improved performance and effects on crystal distribution.

Study of ultrasonic vibration-assisted particle atomic layer deposition process via the CFD-DDPM simulation

Atomic layer deposition (ALD) is a unique surface modification technology by providing conformal ultrathin films on particulate materials. Fluidized bed ALD (FB-ALD) shows excellent scale-up potential for the mass production of particle coating, where different external fields have been developed to enhance the fluidization quality of cohesive micro-nanoparticles. Ultrasonic vibration is a promising assisting method for it can promote effective agglomeration breakage as well as enhance the heat and mass transfer rates in the reactor. In this paper, a multiscale computational fluid dynamics (CFD) simulation based on the dense discrete phase method (DDPM) is developed to study the ultrasonic vibration-assisted FB-ALD process. Dynamic mesh method and discrete element method are adopted to introduce the ultrasonic field and compute the particle movement with an accurate description of particle-particle and particle-vibrating wall interactions. Results show that ultrasonic vibration effectively promotes the contact efficiency between uncoated particles and precursor molecules in the precursor pulsing process, leading to higher deposition rates and coating uniformity. During the purge process, ultrasonic vibration also increases the removal rate of ALD byproducts, thus shortening the purge time by 25%. Through the CFD-DDPM model, the maximum precursor utilization rate for uniform coating can be predicted quantitatively under a given precursor mass fraction and a ratio of the pulse time to the theoretical saturation time. The multiscale numerical model developed in this work can be adapted to optimize the process conditions for the scale-up of FB-ALD reactors.

Shear stress and plaque microenvironment induce heterogeneity: A multiscale microenvironment evolution model

BackgroundBoth clinical images and in vivo observations have demonstrated the heterogeneity in atherosclerotic plaque composition. However, the quantitative mechanisms that contribute to the heterogeneity, such as the wall shear stress (WSS) and the interplays among microenvironmental factors are still unclear. MethodsWe develop a multiscale model coupling computational fluid dynamics, interactions of microenvironmental factors and evolutions of cellular behaviors to investigate the formation of plaque heterogeneity in a three-dimensional vessel segment. The model involves WSS, lipid deposition and inflammatory response to reveal the dynamic balance existed between the lipid metabolism and the phagocytosis of macrophages. ResultsThe dynamic balance in microenvironment is influenced by both the WSS and the interactions with microenvironmental factors, and consequently results in the longitudinal heterogeneity observed in plaque pathology. In addition, plaque heterogeneity can be reduced by decreasing low WSS area at downstream, as well as by altering the phagocytic abilities of macrophage on lipoproteins, which may be used to develop future plaque regression strategies. ConclusionsThis multiscale modeling provides a framework to understand the mechanisms in dynamics of plaque composition and also provides quantitative information to better risk stratification of plaque vulnerability in future clinical practice.

Multiscale CFD Modeling of Area-Selective Atomic Layer Deposition: Application to Reactor Design and Operating Condition Calculation

Area-selective atomic layer deposition (ASALD) as a bottom-up nanopatterning technique has gained recognition for its ability to address misalignment issues in semiconductor manufacturing. This in silico study investigates process operation conditions for ASALD of SiO2/Al2O3 and reactor optimization by using multiscale computational fluid dynamics (CFD) modeling. Several reactor designs were modeled in Ansys Workbench and their results compared to ensure effective reagent separation and homogeneous exposure to reagents across the wafer. Annular reaction zones and asymmetrical inlets enhanced uniform exposure to reagents and minimized reagent intermixing, which allowed the reactor to tolerate higher rotational speeds. Additionally, low rotation speeds and high species mole fractions were required for complete deposition of a cycle of the ASALD process. This research provides insight into the ASALD process operation and contributes to further industrial versatility.

Patient-specific computational simulation of coronary artery bypass grafting.

Coronary artery bypass graft surgery (CABG) is an intervention in patients with extensive obstructive coronary artery disease diagnosed with invasive coronary angiography. Here we present and test a novel application of non-invasive computational assessment of coronary hemodynamics before and after bypass grafting. We tested the computational CABG platform in n = 2 post-CABG patients. The computationally calculated fractional flow reserve showed high agreement with the angiography-based fractional flow reserve. Furthermore, we performed multiscale computational fluid dynamics simulations of pre- and post-CABG under simulated resting and hyperemic conditions in n = 2 patient-specific anatomies 3D reconstructed from coronary computed tomography angiography. We computationally created different degrees of stenosis in the left anterior descending artery, and we showed that increasing severity of native artery stenosis resulted in augmented flow through the graft and improvement of resting and hyperemic flow in the distal part of the grafted native artery. We presented a comprehensive patient-specific computational platform that can simulate the hemodynamic conditions before and after CABG and faithfully reproduce the hemodynamic effects of bypass grafting on the native coronary artery flow. Further clinical studies are warranted to validate this preliminary data.

In-Silico and In-Vitro Analysis of the Novel Hybrid Comprehensive Stage II Operation for Single Ventricle Circulation

Single ventricle (SV) anomalies account for one-fourth of all congenital heart disease cases. The existing palliative treatment for this anomaly achieves a survival rate of only 50%. To reduce the trauma associated with surgical management, the hybrid comprehensive stage II (HCSII) operation was designed as an alternative for a select subset of SV patients with the adequate antegrade aortic flow. This study aims to provide better insight into the hemodynamics of HCSII patients utilizing a multiscale Computational Fluid Dynamics (CFD) model and a mock flow loop (MFL). Both 3D-0D loosely coupled CFD and MFL models have been tuned to match baseline hemodynamic parameters obtained from patient-specific catheterization data. The hemodynamic findings from clinical data closely match the in-vitro and in-silico measurements and show a strong correlation (r = 0.9). The geometrical modification applied to the models had little effect on the oxygen delivery. Similarly, the particle residence time study reveals that particles injected in the main pulmonary artery (MPA) have successfully ejected within one cardiac cycle, and no pathological flows were observed.

A computational framework for guiding the MOCVD-growth of wafer-scale 2D materials

Reproducible wafer-scale growth of two-dimensional (2D) materials using the Chemical Vapor Deposition (CVD) process with precise control over their properties is challenging due to a lack of understanding of the growth mechanisms spanning over several length scales and sensitivity of the synthesis to subtle changes in growth conditions. A multiscale computational framework coupling Computational Fluid Dynamics (CFD), Phase-Field (PF), and reactive Molecular Dynamics (MD) was developed – called the CPM model – and experimentally verified. Correlation between theoretical predictions and thorough experimental measurements for a Metal-Organic CVD (MOCVD)-grown WSe2 model material revealed the full power of this computational approach. Large-area uniform 2D materials are synthesized via MOCVD, guided by computational analyses. The developed computational framework provides the foundation for guiding the synthesis of wafer-scale 2D materials with precise control over the coverage, morphology, and properties, a critical capability for fabricating electronic, optoelectronic, and quantum computing devices.

Machine learning-based run-to-run control of a spatial thermal atomic layer etching reactor

In response to the next technological revolution, atomic layer processes have emerged to produce high-performing, thin-film semiconductor materials. To overcome the long purging times required for conventional atomic layer processes, spatial atomic layer processes have been recognized for their ability to reduce processing times; however, they lack characterization and control. This research aims to construct two novel run-to-run (R2R) control systems using a machine learning model with an artificial neural network (ANN) and an exponentially weighted moving average (EWMA) method for the spatial thermal atomic layer etching (SALE) of aluminum oxide thin films. The two R2R controllers are used in conjunction with a multiscale computational fluid dynamics model of a SALE process with various disturbances to test their effectiveness. Closed-loop simulation results demonstrate that the ANN-based R2R control system reduces etching per cycle variability, maintains the process output within a small region around the setpoint, and outperforms the traditional EWMA-based R2R control system in efficiency.

Multiscale CFD Simulation of an Industrial Diameter-Transformed Fluidized Bed Reactor with Artificial Neural Network Analysis of EMMS Drag Markers

Modeling of gas–solid, heterogeneously catalytic, diameter-transformed fluidized bed (DTFB) reactors is intrinsically complex and requires considering the variation of material properties and operating conditions, because of reactions and/or diameter transformation. The EMMS-matrix drag model, which correlates both operating conditions and local parameters, has been applied in computational fluid dynamics (CFD) simulation of such complex reactors by simplifying the macroscale operating conditions with one set of constant parameters. However, a complete scheme has not been reported that covers a wide range of datasets for a DTFB reactor with complex reactions. To this end, the artificial neural network (ANN), which enables exploring a multivariate relation with the contribution of a set of different parameters, is chosen to couple with EMMS drag modeling. A complete scheme of EMMS-ANN drag for hot, reactive simulation of DTFB is thereby established, with comprehensive evaluation of the contribution of drag markers successively considering the variation of gas properties and operating parameters. Both a priori tests and CFD simulations show that the voidage and slip velocity are the dominant factors in modeling of drag correction, and the effects of dynamic variation of gas properties and operating hydrodynamics are marginal; even the heterogeneous reactions and the change in bed diameter give rise to a remarkable variation in gas properties and operating parameters. The underlying mechanism is then analyzed to provide important clues for drag modeling of gas–solid, heterogeneous catalytic fluidized-bed reactors.

Multiscale computational fluid dynamics modeling of spatial thermal atomic layer etching

Spatial atomic layer deposition and etching processes have emerged to reduce the overall process time while maintaining the conformity of thin films by functioning continuously. This research constructs an multiscale computational fluid dynamics (CFD) model with a dynamic mesh that combines a microscopic kinetic Monte Carlo algorithm of the film etching with a CFD simulation of the gas phase for the spatial thermal atomic layer etching of Al2O3. Using this model, we evaluate the effect that design and operation variables including the gap distance, purge and precursor gas flow rates, substrate velocity, and vacuum pressure have on the substrate film etching per cycle and uniformity. Numerical results suggest that small gap distances with sufficiently high N2 flow are desired to accomplish effective precursor separation for reactor configuration and the process operation requires low substrate velocities and low vacuum pressures to achieve optimal film quality and conformance.