Multiscale Computational Fluid Dynamics Research Articles

Assessment of surface roughness and blood rheology on local coronary haemodynamics: a multi-scale computational fluid dynamics study.

The surface roughness of the coronary artery is associated with the onset of atherosclerosis. The study applies, for the first time, the micro-scale variation of the artery surface to a 3D coronary model, investigating the impact on haemodynamic parameters which are indicators for atherosclerosis. The surface roughness of porcine coronary arteries have been detailed based on optical microscopy and implemented into a cylindrical section of coronary artery. Several approaches to rheology are compared to determine the benefits/limitations of both single and multiphase models for multi-scale geometry. Haemodynamic parameters averaged over the rough/smooth sections are similar; however, the rough surface experiences a much wider range, with maximum wall shear stress greater than 6 Pa compared to the approximately 3 Pa on the smooth segment. This suggests the smooth-walled assumption may neglect important near-wall haemodynamics. While rheological models lack sufficient definition to truly encompass the micro-scale effects occurring over the rough surface, single-phase models (Newtonian and non-Newtonian) provide numerically stable and comparable results to other coronary simulations. Multiphase models allow for phase interactions between plasma and red blood cells which is more suited to such multi-scale models. These models require additional physical laws to govern advection/aggregation of particulates in the near-wall region.

Study of the Mass Transfer–Biodegradation Kinetics in a Pilot-Scale Biotrickling Filter for the Removal of H2S

In this study, a multiscale computational fluid dynamics (CFD) coupled model comprising a macroscopic fluid flow model and microscopic mass transfer-biodegradation kinetics model is developed to ob...

Multiscale Eulerian CFD of Chemical Processes: A Review

This review covers the scope of multiscale computational fluid dynamics (CFD), laying the framework for studying hydrodynamics with and without chemical reactions in single and multiple phases regarded as continuum fluids. The molecular, coarse-grained particle, and meso-scale dynamics at the individual scale are excluded in this review. Scoping single-scale Eulerian CFD approaches, the necessity of multiscale CFD is highlighted. First, the Eulerian CFD theory, including the governing and turbulence equations, is described for single and multiple phases. The Reynolds-averaged Navier–Stokes (RANS)-based turbulence model such as the standard k-ε equation is briefly presented, which is commonly used for industrial flow conditions. Following the general CFD theories based on the first-principle laws, a multiscale CFD strategy interacting between micro- and macroscale domains is introduced. Next, the applications of single-scale CFD are presented for chemical and biological processes such as gas distributors, combustors, gas storage tanks, bioreactors, fuel cells, random- and structured-packing columns, gas-liquid bubble columns, and gas-solid and gas-liquid-solid fluidized beds. Several multiscale simulations coupled with Eulerian CFD are reported, focusing on the coupling strategy between two scales. Finally, challenges to multiscale CFD simulations are discussed. The need for experimental validation of CFD results is also presented to lay the groundwork for digital twins supported by CFD. This review culminates in conclusions and perspectives of multiscale CFD.

Personalized Dosimetry for Liver Cancer Y-90 Radioembolization Using Computational Fluid Dynamics and Monte Carlo Simulation.

Yttrium-90 (Y-90) transarterial radioembolization uses radioactive microspheres injected into the hepatic artery to irradiate liver tumors internally. One of the major challenges is the lack of reliable dosimetry methods for dose prediction and dose verification. We present a patient-specific dosimetry approach for personalized treatment planning based on computational fluid dynamics (CFD) simulations of the microsphere transport combined with Y-90 physics modeling called CFDose. The ultimate goal is the development of a software to optimize the amount of activity and injection point for optimal tumor targeting. We present the proof-of-concept of a CFD dosimetry tool based on a patient's angiogram performed in standard-of-care planning. The hepatic arterial tree of the patient was segmented from the cone-beam CT (CBCT) to predict the microsphere transport using multiscale CFD modeling. To calculate the dose distribution, the predicted microsphere distribution was convolved with a Y-90 dose point kernel. Vessels as small as 0.45mm were segmented, themicrosphere distribution between the liver segments using flow analysis was predicted,the volumetric microsphere and resulting dose distribution in the liver volume were computed. The patient was imaged with positron emission tomography (PET) 2h after radioembolization to evaluate the Y-90 distribution. The dose distribution was found to be consistent with the Y-90 PET images. These results demonstrate the feasibility of developing a complete framework for personalized Y-90 microsphere simulation and dosimetry using patient-specific input parameters.

Effects of plasma kinetic modeling on performance characterization of plasma actuators for active flow control

This work focuses on the development of a multiscale computational fluid dynamics (CFD) simulation framework for the investigation of the effects of plasma kinetics on the performance of a microscale dielectric barrier discharge plasma actuator (DBD-PA). To this purpose, DBD-PA multi-scale dual-step modelling approach has been implemented, by considering plasma chemistry and flow dynamic. At first, a microscopic plasma model based on the air plasma kinetics has been defined and plasma reactions have been simulated in zero-dimensional computations in order to evaluate the charge density. At this aim computations have been performed using the toolbox ZDPlasKin, which solves plasma reactions by means of Bolsig+ solver. An alternate current (AC) electrical feeding has been assumed: in particular, the sinusoidal voltage amplitude and the frequency have been fixed at 5 kV and 1 kHz at atmospheric pressure and 300 K temperature in quiescent environment. The predictal charge density has been in a macroscopic plasma-fluid model based on Suzen Dual Potential Model (DPM), which has implemented in the computation fluid dynamic CFD code OpenFoam. Hence, as second step, 2D-CFD simulations of the electro-hydrodynamic body forces induced by the microscale DBDPA have been performed, based on the previously predicted charge densities at the operating conditions. Quiescent flow over a dielectric barrier discharge actuator has been simulated using the plasma-fluid model. The novel modelling framework has been validated with experimental data.

Multi-phase particle-in-cell coupled with population balance equation (MP-PIC-PBE) method for multiscale computational fluid dynamics simulation

The ‘multiphase particle-in-cell coupled with population balance equation’ (MP-PIC-PBE) method is introduced for simulating multi-scale multiphase particulate flows. This method couples the meso‑scale fluid dynamics simulated by the MP-PIC method with the simulation of the micro-scale particle size distribution. The homogeneous population balance equation is calculated for each discrete particle tracked in a Lagrangian frame, after the MP-PIC numerical procedure is followed at each time instance. This approach allows the particulate phase to accommodate the particulate stresses using spatial gradients and allows the Lagrangian description to predict particle properties by the PBE. For the antisolvent crystallization of Lovastatin in a biradial mixer, the proposed method is compared to an existing method that simulates the spatiotemporal evolution of the particle distribution by combining a multi-environment probability density function with the spatially varying PBE. The MP-PIC-PBE method has lower computational cost and provides more detailed information, such as particle age and location.

Integrating Feedback Control and Run-to-Run Control in Multi-Wafer Thermal Atomic Layer Deposition of Thin Films

There is currently a lack of understanding of the deposition profile in a batch atomic layer deposition (ALD) process. Also, no on-line control scheme has been proposed to resolve the prevalent disturbances. Motivated by this, we develop a computational fluid dynamics (CFD) model and an integrated online run-to-run and feedback control scheme. Specifically, we analyze a furnace reactor for a SiO2 thin-film ALD with BTBAS and ozone as precursors. Initially, a high-fidelity 2D axisymmetric multiscale CFD model is developed using ANSYS Fluent for the gas-phase characterization and the surface thin-film deposition, based on a kinetic Monte-Carlo (kMC) model database. To deal with the disturbance during reactor operation, a proportional integral (PI) control scheme is adopted, which manipulates the inlet precursor concentration to drive the precursor partial pressure to the set-point, ensuring the complete substrate coverage. Additionally, the CFD model is utilized to investigate a wide range of operating conditions, and a regression model is developed to describe the relationship between the half-cycle time and the feed flow rate. A run-to-run (R2R) control scheme using an exponentially weighted moving average (EWMA) strategy is developed to regulate the half-cycle time for the furnace ALD process between batches.

Simulation-Based Design and Economic Evaluation of a Novel Internally Circulating Fluidized Bed Reactor for Power Production with Integrated CO2 Capture

Limiting global temperature rise to well below 2 °C according to the Paris climate accord will require accelerated development, scale-up, and commercialization of innovative and environmentally friendly reactor concepts. Simulation-based design can play a central role in achieving this goal by decreasing the number of costly and time-consuming experimental scale-up steps. To illustrate this approach, a multiscale computational fluid dynamics (CFD) approach was utilized in this study to simulate a novel internally circulating fluidized bed reactor (ICR) for power production with integrated CO2 capture on an industrial scale. These simulations were made computationally feasible by using closures in a filtered two-fluid model (fTFM) to model the effects of important subgrid multiphase structures. The CFD simulations provided valuable insight regarding ICR behavior, predicting that CO2 capture efficiencies and purities above 95% can be achieved, and proposing a reasonable reactor size. The results from the reactor simulations were then used as input for an economic evaluation of an ICR-based natural gas combined cycle power plant. The economic performance results showed that the ICR plant can achieve a CO2 avoidance cost as low as $58/ton. Future work will investigate additional firing after the ICR to reach the high inlet temperatures of modern gas turbines.

Impacts of Internal Carotid Artery Revascularization on Flow in Anterior Communicating Artery Aneurysm: A Preliminary Multiscale Numerical Investigation

The optimal management strategy of patients with concomitant anterior communicating artery aneurysm (ACoAA) and internal carotid artery (ICA) stenosis is unclear. This study aims to evaluate the impacts of unilateral ICA revascularization on hemodynamics factors associated with rupture in an ACoAA. In the present study, a multiscale computational model of ACoAA was developed by coupling zero-dimensional (0D) models of the cerebral vascular system with a three-dimensional (3D) patient-specific ACoAA model. Distributions of flow patterns, wall shear stress (WSS), relative residence time (RRT) and oscillating shear index (OSI) in the ACoAA under left ICA revascularization procedure were quantitatively assessed by using transient computational fluid dynamics (CFD) simulations. Our results showed that the revascularization procedures significantly changed the hemodynamic environments in the ACoAA. The flow disturbance in the ACoAA was enhanced by the resumed flow from the affected side. In addition, higher OSI (0.057 vs. 0.02), prolonged RRT (1.14 vs. 0.39) and larger low WSS area (66 vs. 50 mm2) in ACoAA were found in the non-stenotic case. These acute changes in hemodynamics after revascularization may elevate the rupture risk of ACoAA. The preliminary results validated the feasibility of predicting aneurismal hemodynamics characteristics in revascularization procedures by using multiscale CFD simulations, which would benefit the management of this group of patients.

Multiscale modelling of mass transfer in gas jets and bubble plumes

AbstractThe injection of high‐speed gas streams into liquids is common in many industrial applications, such as sparging in multiphase reactors and contacting in mass transfer devices. Modelling the fluid dynamics and associated heat and mass transfer processes in such a system is complex because it involves many governing scales and drastic changes in physical properties. In this study, one formulation of a multiscale computational fluid dynamics model is proposed to simulate the fluid dynamics and mass transfer in such systems. The model uses volume‐of‐fluid interface capturing in regions where high mesh resolution can be attained and the drift‐flux or mixture model approximation in regions where mesh resolution is too low to directly resolve interface dynamics. The model was developed to provide a tunable, automatic transition between the two modelling approaches for both fluid dynamics and mass transfer predictions. The approach was validated through a comparison with results from two published studies. In the first case, the implementation of the drift‐flux model was validated through the simulation of a dispersed gas bubble plume injected into a cylindrical tank. In the second case, the fluid dynamics and mass transfer predictions were compared to results from an experimental study involving the horizontal injection of air into a rectangular tank filled with water for the application of aeration. The results show that the modelling approach can provide a good prediction of the experimental data using only limited fitting of empirical parameters, making it applicable to a broad range of other applications.

Machine learning-based modeling and operation for ALD of SiO2 thin-films using data from a multiscale CFD simulation

Atomic layer deposition (ALD) is a widely utilized deposition technology in the semiconductor industry due to its superior ability to generate highly conformal films and to deposit materials into high aspect-ratio geometric structures. However, ALD experiments remain expensive and time-consuming, and the existing first-principles based models have not yet been able to provide solutions to key process outputs that are computationally efficient, which is necessary for on-line optimization and real-time control. In this work, a multiscale data-driven model is proposed and developed to capture the macroscopic process domain dynamics with a linear parameter varying model, and to characterize the microscopic domain film growth dynamics with a feed-forward artificial neural network (ANN) model. The multiscale data-driven model predicts the transient deposition rate from the following four key process operating parameters that can be manipulated, measured or estimated by process engineers: precursor feed flow rate, operating pressure, surface heating, and transient film coverage. Our results demonstrate that the multiscale data-driven model can efficiently characterize the transient input-output relationship for the SiO2 thermal ALD process using bis(tertiary-butylamino)silane (BTBAS) as the Si precursor. The multiscale data-driven model successfully reduces the computational time from 0.6 to 1.2h for each time step, which is required for the first-principles based multiscale computational fluid dynamics (CFD) model, to less than 0.1s, making its real-time usage feasible. The developed data-driven modeling methodology can be further generalized and used for other thermal ALD or similar deposition systems, which will greatly enhance the feasibility of industrial manufacturing processes.

Multiscale Computational Fluid Dynamics

Computational Fluid Dynamics (CFD) has numerous applications in the field of energy research, in modelling the basic physics of combustion, multiphase flow and heat transfer; and in the simulation of mechanical devices such as turbines, wind wave and tidal devices, and other devices for energy generation. With the constant increase in available computing power, the fidelity and accuracy of CFD simulations have constantly improved, and the technique is now an integral part of research and development. In the past few years, the development of multiscale methods has emerged as a topic of intensive research. The variable scales may be associated with scales of turbulence, or other physical processes which operate across a range of different scales, and often lead to spatial and temporal scales crossing the boundaries of continuum and molecular mechanics. In this paper, we present a short review of multiscale CFD frameworks with potential applications to energy problems.

Multi-Scale CFD Modeling of Plate Heat Exchangers Including Offset-Strip Fins and Dimple-Type Turbulators for Automotive Applications

Plate heat exchangers including offset-strip fins or dimple-type turbulators have a wide application in the automotive field as oil coolers for internal combustion engines and transmissions. Their optimization is a complex task since it requires targeting different objectives: High compactness, low pressure drop and high heat-transfer efficiency. In this context, the availability of accurate Computational Fluid Dynamics (CFD) simulation models plays an important role during the design phase. In this work, the development of a computational framework for the CFD simulation of compact oil-to-liquid heat exchangers, including offset-strip fins and dimples, is presented. The paper addresses the modeling problem at different scales, ranging from the characteristic size of the turbulator geometry (typically µm–mm) to the full scale of the overall device (typically cm–dm). The simulation framework is based on multi-scale concept, which applies: (a) Detailed simulations for the characterization of the micro-scale properties of the turbulator, (b) an upscaling approach to derive suitable macro-scale models for the turbulators and (c) full-scale simulations of the entire cooler, including the porous models derived for the smaller scales. The model is validated comparing with experimental data under different operating conditions. Then, it is adopted to investigate the details of the fluid dynamics and heat-transfer process, providing guidelines for the optimization of the device.

A multiscale computational fluid dynamics approach to simulate the micro-fluidic environment within a tissue engineering scaffold with highly irregular pore geometry

Mechanical stimulation can regulate cellular behavior, e.g., differentiation, proliferation, matrix production and mineralization. To apply fluid-induced wall shear stress (WSS) on cells, perfusion bioreactors have been commonly used in tissue engineering experiments. The WSS on cells depends on the nature of the micro-fluidic environment within scaffolds under medium perfusion. Simulating the fluidic environment within scaffolds will be important for gaining a better insight into the actual mechanical stimulation on cells in a tissue engineering experiment. However, biomaterial scaffolds used in tissue engineering experiments typically have highly irregular pore geometries. This complexity in scaffold geometry implies high computational costs for simulating the precise fluidic environment within the scaffolds. In this study, we propose a low-computational cost and feasible technique for quantifying the micro-fluidic environment within the scaffolds, which have highly irregular pore geometries. This technique is based on a multiscale computational fluid dynamics approach. It is demonstrated that this approach can capture the WSS distribution in most regions within the scaffold. Importantly, the central process unit time needed to run the model is considerably low.

Multiscale computational fluid dynamics modeling of thermal atomic layer deposition with application to chamber design

This work develops a first-principles-based three-dimensional, multiscale computational fluid dynamics (CFD) model, together with reactor geometry optimizations, of SiO2 thin-film thermal atomic layer deposition (ALD) using bis(tertiary-butylamino)silane (BTBAS) and ozone as precursors. Specifically, an accurate macroscopic CFD model of the ALD reactor chamber gas-phase development is integrated with a detailed microscopic kinetic Monte Carlo (kMC) model that was developed in Ding et al. (2019), accounting for the microscopic lattice structure, atomic interactions and detailed surface chemical reactions. The multiscale information exchange and the transient simulation of the microscopic distributed kMC algorithms and the macroscopic CFD model are achieved through a parallel processing message passing interface (MPI) structure. Additionally, density functional theory (DFT)-based calculations are adopted to compute the key thermodynamic and kinetic parameters for the microscopic thin-film growth process. Recognizing the transient non-uniformity and the possibility to reduce the current ALD cycle time, the optimal configuration of reactor geometry is designed and evaluated including a showerhead panel adjustment and geometry modifications on reactor inlet and upstream. It is demonstrated that with suitable reactor chamber design the required BTBAS ALD half-cycle time can be reduced by 39.6%.

A Hybrid Experimental-Computational Modeling Framework for Cardiovascular Device Testing.

Significant advances in biomedical science often leverage powerful computational and experimental modeling platforms. We present a framework named physiology simulation coupled experiment ("PSCOPE") that can capitalize on the strengths of both types of platforms in a single hybrid model. PSCOPE uses an iterative method to couple an in vitro mock circuit to a lumped-parameter numerical simulation of physiology, obtaining closed-loop feedback between the two. We first compared the results of Fontan graft obstruction scenarios modeled using both PSCOPE and an established multiscale computational fluid dynamics method; the normalized root-mean-square error values of important physiologic parameters were between 0.1% and 2.1%, confirming the fidelity of the PSCOPE framework. Next, we demonstrate an example application of PSCOPE to model a scenario beyond the current capabilities of multiscale computational methods-the implantation of a Jarvik 2000 blood pump for cavopulmonary support in the single-ventricle circulation; we found that the commercial Jarvik 2000 controller can be modified to produce a suitable rotor speed for augmenting cardiac output by approximately 20% while maintaining blood pressures within safe ranges. The unified modeling framework enables a testing environment which simultaneously operates a medical device and performs computational simulations of the resulting physiology, providing a tool for physically testing medical devices with simulated physiologic feedback.

Multiscale CFD modelling and analysis of TBR behavior for an HDS process: Deviations from ideal behaviors

For the hydrotreatment process of petroleum cuts, there is a great diversity and level of Trickle Bed Reactors (TBR) models, in which it is very common to use important simplifications, such as the consideration of plug flow; these simplifications restrict the analysis of the multiphysics and multiscale nature of the phenomena that take place in such systems. The analysis of the phenomena that take place at different scales in the TBRs is very scarce; moreover, the qualitative and quantitative determination of the information that passes from one to another scale and its influence on the mass transport nature in these systems is even more difficult to find. With the purpose of analyzing the multiphysic and multiscale nature of a reactor for an HDS process, three Computational Fluid Dynamics (CFD) models were studied at three different scales, corresponding to: (i) Heterogeneous micropores model (HMM) for a particle with explicit representation of the internal surface microstructure of the catalyst, (ii) Pseudohomogeneous catalyst particle model (PCM), and (iii) Reactor scale model (RSM). The objective sought is to establish the validity of some of the assumptions commonly made in the simulation of these types of reactors and develop an analysis to determine the importance of establishing bridges of information between the phenomena that take place at different scales. The results show that despite the small dimensions of the reactor, the plug flow assumptions might not be valid, due to the presence of strong radial gradients. It was also determined that the models that do not take into account the communication between scales (catalysts to reactor scale) differ substantially from those that do, which can be verified by the differences found for the effectiveness factors, of around 35%.

The Influence of Rotary Blood Pump Speed Modulation on the Risk of Intraventricular Thrombosis.

Rotary left ventricular assist devices (LVADs) are commonly operated at a constant speed, attenuating blood flow pulsatility. Speed modulation of rotary LVADs has been demonstrated to improve vascular pulsatility and pump washout. The effect of LVAD speed modulation on intraventricular flow dynamics is not well understood, which may have an influence on thromboembolic events. This study aimed to numerically evaluate intraventricular flow characteristics with a speed modulated LVAD. A severely dilated anatomical left ventricle was supported by a HeartWare HVAD in a three-dimensional multiscale computational fluid dynamics model. Three LVAD operating scenarios were evaluated: constant speed and sinusoidal co- and counter-pulsation. In all operating scenarios, the mean pump speed was set to restore the cardiac output to 5.0L/min. Co- and counter-pulsation was speed modulated with an amplitude of 750rpm. The risk of thrombosis was evaluated based on blood residence time, ventricular washout, kinetic energy densities, and a pulsatility index map. Blood residence time for co-pulsation was on average 1.8 and 3.7% lower than constant speed and counter-pulsation mode, respectively. After introducing fresh blood to displace preexisting blood for 10 cardiac cycles, co-pulsation had 1.5% less old blood in comparison to counter-pulsation. Apical energy densities were 84 and 27% higher for co-pulsation in comparison to counter-pulsation and constant speed mode, respectively. Co-pulsation had an increased pulsatility index around the left ventricular outflow tract and mid-ventricle. Improved flow dynamics with co-pulsation was caused by increased E-wave velocities which minimized blood stasis. In the studied scenario and from the perspective of intraventricular flow dynamics, co-pulsation of rotary LVADs could minimize the risk of intraventricular thrombosis.

Patient-specific multiscale computational fluid dynamics assessment of embolization rates in the hybrid Norwood: effects of size and placement of the reverse Blalock-Taussig shunt.

The hybrid Norwood operation is performed to treat hypoplastic left heart syndrome. Distal arch obstruction may compromise flow to the brain. In a variant of this procedure, a synthetic graft (reverse Blalock-Taussig shunt) is placed between the pulmonary trunk and innominate artery to improve upper torso blood flow. Thrombi originating in the graft may embolize to the brain. In this study, we used computational fluid dynamics and particle tracking to investigate the patterns of particle embolization as a function of the anatomic position of the reverse Blalock-Taussig shunt. The degree of distal arch obstruction and position of particle origin influence embolization probabilities to the cerebral arteries. Cerebral embolization probabilities can be reduced by as much as 20% by optimizing graft position, for a given arch geometry, degree of distal arch obstruction, and particle origin. There is a tradeoff, however, between cerebral pulmonary and coronary embolization probabilities.

Prediction of degree of impregnation in thermoplastic unidirectional carbon fiber prepreg by multi-scale computational fluid dynamics

A multi-scale simulation approach was proposed to predict the degree of impregnation (DoI) in thermoplastic unidirectional carbon fiber prepreg (UD-CFP). The multi-scale approach included a two-dimensional (2D) micro-scale computational fluid dynamics (CFD) in a representative elementary volume (REV) of carbon fiber (CF) tow, a 3D macro-scale CFD of an entire impregnation die with 15 sliding CF tows, and a process-scale simulation assembling data from the micro- and macro-scale CFDs. In the macro-scale steady-state CFD, thermoplastic resin injection and CF tow insertion were considered for an impregnation die 10 cm in width. In the micro-scale transient CFD, impregnation mechanisms of resin into CF filaments 7 μm in diameter were identified in terms of surface coverage, capillary permeation, and penetration through CF filaments. The DoI as a function of pressure and time was obtained from the micro-scale CFD within a range of pressures found in the macro-scale CFD. In the process-scale simulation, the cumulative DoI of the 15 tows was predicted along the impregnation die length with the aid of the micro- and macro-scale CFD results. Combining the multi-scale models gives a potential to predict the uniformity of the transverse resin amount in the final UD-CFP product.