Porous Media Computational Fluid Dynamics Research Articles

Flow and mass transfer prediction in anisotropic TPMS-structures as extracorporeal oxygenator membranes using reduced order modeling

Currently, hollow fiber membranes are the standard technology for extracorporeal membrane oxygenators. Apart from the inevitable contact of the circulating blood with the artificial material, a suboptimal flow distribution within the oxygenator favors thrombus formation which leads to a rapid loss of gas exchange capacity. The current advancement in additive manufacturing allows the design of three-dimensional membrane-structures, based on triply periodic minimal surfaces (TPMS). One of their unique advantages is local geometry variation to manipulate the flow distribution. But how this anisotropy influences the overall device performance is non-trivial and requires numerical simulation. The aim of this study was to develop a reduced order model (ROM) that is able to efficiently predict three-dimensional flow distribution and gas transfer inside TPMS-structures. We performed a parametric study using a validated micro scale computational fluid dynamics (CFD) model. Afterwards, two different modeling approaches of Sherwood-correlations and artificial neural networks (NN) were compared to characterize flow and mass transfer from the simulated data. To create the ROM, the NN modeling strategy was then implemented into a porous medium CFD model. The developed ROM was also validated. Finally, an anisotropic TPMS-membrane-structure was compared numerically with an isotropic predicate. The NN fitting strategy showed superior accuracy over the Sherwood-correlations for characterizing mass transfer in TPMS-structures. With the ROM, the gas transfer rates of oxygen and carbon dioxide from the micro CFD model could be predicted within relative root mean squared errors (RRMSE) of 2.7% and 5.1%. The pressure drop in the experiments was predicted with an RRMSE accuracy of 7.6%. In comparison with the isotropic TPMS-structure, the anisotropic structure showed a homogenized flow distribution and increased gas transfer rates of 4% to 5% for oxygen and 2.3% to 7.4% for carbon dioxide at the simulated flow rates.

Numerical simulation of a precision air conditioner under variable working conditions

Artificial intelligence (AI)-based intelligent working parameter setting of cooling equipment is a promising strategy for energy savings in large data centers. For this purpose, the performance curves of each piece of equipment must be obtained under variable working conditions. In the present study, a porous media computational fluid dynamics (CFD) model was established to investigate the flow and thermal performance of a finned-tube heat exchanger in a precision air conditioner (PAC) of a large data center with 3000 server racks. The temperature and velocity at the air outlet of the PAC were measured at 15 measurement points, and the results agreed well with the simulation results with a difference less than 10%. Under various inlet temperatures and flow rates of both chilled water and air, the heat transfer rate and pressure drop were studied. From the viewpoint of economical operation of the PAC, a critical flow rate was revealed for water and air, respectively. In addition, empirical formulas of the heat transfer rate of the PAC were obtained, which can facilitate energy savings by determining the optimized temperature of the chilled water and operating parameters of the pump and fan.

Numerical study on heat and mass transfer characteristics in a randomly packed air cooling tower for large-scale air separation systems

To investigate the heat and mass transfer characteristics of the moist air–water counter-current flow in a randomly packed air cooling tower (RPACT) for large-scale air separation units, a 3-D Eulerian porous media computational fluid dynamics (CFD) model coupled with mass transfer equations was developed. A plastic Super ring (model 50-RLF1), with the highest porous resistance of the candidate materials, was selected as the optimal packing material for the RPACT. The effects of operating conditions and packing characteristics on the flow and coupled heat–mass transfer performance were analyzed, including pressure drop, liquid holdup, fluid temperature, wall film flow rate, humidity ratio, and the total heat transfer rate of the RPACT. Through model validation, it was found that the 3-D Eulerian porous media model built in this study can accurately predict the RPACT performance and is suitable for the configuration design and optimization. The investigation results show that both the F-factor and liquid load sensitively influence the performance, and there is an optimum range of operating conditions. The total heat transfer rate of the RPACT is 0.84% greater than the rated value designed by an industrial gas equipment producer, even with a packing depth reduced to 6 m from the designed value (8 m).

Porous Media Computational Fluid Dynamics and the Role of the First Coil in the Embolization of Ruptured Intracranial Aneurysms.

Background: The objective of our project was to identify a late recanalization predictor in ruptured intracranial aneurysms treated with coil embolization. This goal was achieved by means of a statistical analysis followed by a computational fluid dynamics (CFD) with porous media modelling approach. Porous media CFD simulated the hemodynamics within the aneurysmal dome after coiling. Methods: Firstly, a retrospective single center analysis of 66 aneurysmal subarachnoid hemorrhage patients was conducted. The authors assessed morphometric parameters, packing density, first coil volume packing density (1st VPD) and recanalization rate on digital subtraction angiograms (DSA). The effectiveness of initial endovascular treatment was visually determined using the modified Raymond–Roy classification directly after the embolization and in a 6- and 12-month follow-up DSA. In the next step, a comparison between porous media CFD analyses and our statistical results was performed. A geometry used during numerical simulations based on a patient-specific anatomy, where the aneurysm dome was modelled as a separate, porous domain. To evaluate hemodynamic changes, CFD was utilized for a control case (without any porosity) and for a wide range of porosities that resembled 1–30% of VPD. Numerical analyses were performed in Ansys CFX solver. Results: A multivariate analysis showed that 1st VPD affected the late recanalization rate (p < 0.001). Its value was significantly greater in all patients without recanalization (p < 0.001). Receiver operating characteristic curves governed by the univariate analysis showed that the model for late recanalization prediction based on 1st VPD (AUC 0.94 (95%CI: 0.86–1.00) is the most important predictor of late recanalization (p < 0.001). A cut-off point of 10.56% (sensitivity—0.722; specificity—0.979) was confirmed as optimal in a computational fluid dynamics analysis. The CFD results indicate that pressure at the aneurysm wall and residual flow volume (blood volume with mean fluid velocity > 0.01 m/s) within the aneurysmal dome tended to asymptotically decrease when VPD exceeded 10%. Conclusions: High 1st VPD decreases the late recanalization rate in ruptured intracranial aneurysms treated with coil embolization (according to our statistical results > 10.56%). We present an easy intraoperatively calculable predictor which has the potential to be used in clinical practice as a tip to improve clinical outcomes.

Investigation of Flow Behavior and Porous Medium Resistance Coefficients for Metallic-Cloth Fibers

The flow through porous metallic-cloth fibers influences the cloth seal leakage performance. Measuring the actual seal leakage proves difficult with challenging turbine operating conditions. A non-Darcian porous medium Computational Fluid Dynamics (CFD) model was employed for the flow within porous metallic-cloth fibers. CFD analyses need leakage data depending on the pressure load to calibrate flow resistance coefficients. A test rig was built to measure leakage with respect to the pressure load and weave orientation in four directions. The Sutherland-ideal gas approach was utilized to determine the flow resistance coefficients for Dutch twill metallic-cloth fibers as a function of pressure load. The results show that metallic-cloth fiber leakage is a linear function of pressure load. The best–worst order for leakage performance was the warp, diagonal, shute, and cross directions. For the best sealing performance, the flow direction in metallic-cloth fibers would be the warp direction. The flow resistance coefficients depend on the evaluation of the pressure level, which changes over the weave flow thickness. This is represented with the pressure constant (Cdown). The best match between the test and CFD leakages was obtained for the weave directions of warp (0.9), shute (0.9), diagonal (0.7), and cross (0.0). Calibrating the resistance coefficients with respect to the pressure and temperature enables performing CFD analyses in turbine conditions.

Research on the Integrated Intercooler Intake System of Turbocharged Diesel Engine

In order to improve the compactness and performance of the intake system of turbocharged diesel engines, an integrated intercooler intake system is provided. Porous media computational fluid dynamics (CFD) model is used to analyze the flow and heat exchange performance of the integrated intercooler. The flow resistance, pressure fluctuation, temperature and pressure distribution of integrated intercoolers with different structures are compared by CFD simulation. The simulation results show that the best performance is achieved by the structure with central air intake with a baffle. Experimental study has been carried out to investigate the steady and transient performance of diesel engine with the original or integrated intercooler intake system. The test results show that with the use of the integrated intercooler intake system, the brake specific fuel consumption can be reduced by 5.9 g/kW·h at the rated condition, and the response time is reduced by 20.4 % under medium speed loading process.

Computational fluid dynamics (CFD) using porous media modeling predicts recurrence after coiling of cerebral aneurysms.

ObjectiveThis study aimed to predict recurrence after coil embolization of unruptured cerebral aneurysms with computational fluid dynamics (CFD) using porous media modeling (porous media CFD).MethodA total of 37 unruptured cerebral aneurysms treated with coiling were analyzed using follow-up angiograms, simulated CFD prior to coiling (control CFD), and porous media CFD. Coiled aneurysms were classified into stable or recurrence groups according to follow-up angiogram findings. Morphological parameters, coil packing density, and hemodynamic variables were evaluated for their correlations with aneurysmal recurrence. We also calculated residual flow volumes (RFVs), a novel hemodynamic parameter used to quantify the residual aneurysm volume after simulated coiling, which has a mean fluid domain > 1.0 cm/s.ResultFollow-up angiograms showed 24 aneurysms in the stable group and 13 in the recurrence group. Mann-Whitney U test demonstrated that maximum size, dome volume, neck width, neck area, and coil packing density were significantly different between the two groups (P < 0.05). Among the hemodynamic parameters, aneurysms in the recurrence group had significantly larger inflow and outflow areas in the control CFD and larger RFVs in the porous media CFD. Multivariate logistic regression analyses demonstrated that RFV was the only independently significant factor (odds ratio, 1.06; 95% confidence interval, 1.01–1.11; P = 0.016).ConclusionThe study findings suggest that RFV collected under porous media modeling predicts the recurrence of coiled aneurysms.

Simulation of phenol biodegradation by Ralstonia eutropha in a packed-bed bioreactor with batch recycle mode using CFD technique

Packed-bed reactors are widely used in biological treatment processes. The complete simulation of the reactions and concentration profiles of the reactors, which are necessary for a successful reactor design, operation, and scale-up, are now possible due to extensive improvements of numerical methods and computational power. In the present work, phenol biodegradation was studied in a packed-bed bioreactor operating in the recycling batch mode using the computational fluid dynamics (CFD) method. A transient comprehensive 3D CFD was developed to simulate the dynamic behavior of batch phenol biodegradation by Ralstonia eutropha in a Kissiris-immobilized cell bioreactor. The model combined the porous medium CFD model with two kinetic equations, namely the Haldane and Luong inhibition models, to consider the inhibitory effect of phenol at high concentrations. The simulation results of the phenol concentration variation in different initial phenol concentrations (2.13, 4.26, 6.39, and 8.52mol/m3) and recirculation flow rates (10, 25, and 40ml/min) were validated against experimental data. Despite the assumptions, the simulation results create an acceptable assurance of the simulation precision with good agreement with experimental data.

Combination of adsorption-diffusion model with CFD for study of desulfurization in fixed bed

A 2D porous media Computational Fluid Dynamics (CFD) model is developed for a fixed bed adsorber to remove the 4,6-dimethyldibenzothiophene (4,6-DMDBT) from diesel. The Ag-TiO2-SiO2 modified by CeOx adsorbent is used to remove the 4,6-DMDBT from diesel and proves that CeOx species could promote high dispersion of Ag species on adsorbent surface. The mass source term describing mass transfer of 4,6-DMDBT inside the adsorption bed column is considered. The effects of various parameters such as feed concentration, feed rate and column height on adsorption process have been investigated. Mesh independent test is performed to investigate the effect of the grid size on the simulation results. The component distribution contour and mass transfer rate are employed to analyse further the mass transfer phenomenon in fixed bed column. The higher mass transfer rate at the beginning can be observed and the lower mass transfer rate is obtained after a period of adsorption time at high feed concentration. Results also demonstrate that the porous media CFD model can successfully describe the adsorption of 4,6-DMDBT from diesel in fixed bed column. Finally, the results of Genetic algorithm search suggest that the optimal height of mass transfer zone can be got at low feed rate, high bed height and low feed concentration.

Experimental Validation of the Aerodynamic Characteristics of an Aero-engine Intercooler

Porous media model computational fluid dynamics (CFD) is a valuable approach allowing an entire heat exchanger system, including the interactions with its associated installation ducts, to be studied at an affordable computational effort. Previous work of this kind has concentrated on developing the heat transfer and pressure loss characteristics of the porous medium model. Experimental validation has mainly been based on the measurements at the far field from the porous media exit. Detailed near field data are rare. In this paper, the fluid dynamics characteristics of a tubular heat exchanger concept developed for aero-engine intercooling by the authors are presented. Based on a rapid prototype manufactured design, the detailed flow field in the intercooler system is recorded by particle image velocimetry (PIV) and pressure measurements. First, the computational capability of the porous media to predict the flow distribution within the tubular heat transfer units was confirmed. Second, the measurements confirm that the flow topology within the associated ducts can be described well by porous media CFD modeling. More importantly, the aerodynamic characteristics of a number of critical intercooler design choices have been confirmed, namely, an attached flow in the high velocity regions of the in-flow, particularly in the critical region close to the intersection and the in-flow guide vane, a well-distributed flow in the two tube stacks, and an attached flow in the cross-over duct.

Effect of ship tilting and motion on amine absorber with structured‐packing for CO2 removal from natural gas

A gas‐liquid Eulerian porous media computational fluid dynamics (CFD) model was developed for an absorber with structured packing to remove CO2 from natural gas by mono‐ethanol‐amine (MEA). The three‐dimensional geometry of the amine absorber with Mellapak 500.X was constructed to investigate the effect of the tilting and motion experienced on ships and barges for offshore plants. The momentum equation included porous resistance, gas‐liquid momentum exchange, and liquid dispersion to replace structured‐packing by porous media. The mass equation involved mass transfer of CO2 gas into MEA solution, and one chemical reaction. Parameters of the CFD model were adjusted to fit experimental data measured in the CO2‐MEA system. As the tilting angle increased, the liquid holdup and effective interfacial area decreased and CO2 removal efficiency was lowered. The uniformity of liquid holdup deteriorated by 10% for a 3° static tilting, and a rolling motion with 4.5° amplitude and 12 s period, respectively. © 2015 American Institute of Chemical Engineers AIChE J, 61: 4412–4425, 2015

Porous media Eulerian computational fluid dynamics (CFD) model of amine absorber with structured-packing for CO2 removal

A gas–liquid Eulerian porous media computational fluid dynamics (CFD) model was developed for an absorber to remove CO2 from natural gas by mono-ethanol-amine (MEA). The three dimensional geometry of the amine absorber packed with nine elements of Mellapak 500.X (M500X) was constructed for the CFD domain. The momentum conservation equation included the porous resistance, gas–liquid momentum exchange and liquid dispersion to replace the structured-packing by the porous media model. The mass conservation equation involved the mass transfer of CO2 gas into the MEA solution and one chemical reaction. The mesh independent test was performed on coarse, medium and fine meshes and the medium mesh (37,400 cells) was selected for further investigation. Parameters of the CFD model were adjusted to fit experimental data (wet pressure drop, liquid holdup, and CO2 mole fraction along the column height) measured in a CO2-MEA system on M500X. This study demonstrated that the porous media CFD model can treat both hydrodynamics and CO2 removal in the amine absorber with structured-packing.

CFD-Based Analysis of 1-MCP Distribution in Commercial Cool Store Rooms: Porous Medium Model Application

1-Methylcyclopropene (1-MCP) is a synthetic plant growth regulator used commercially to delay ripening of fruits. 1-MCP (SmartFreshTM) is applied in gaseous form (as a fumigant) in the cool store room. This paper uses a porous medium computational fluid dynamics model to numerically analyze the distribution of 1-MCP in cool store rooms for apple fruit. The effects of air circulation, room shape, and bin material were investigated. Dose calculation based on filling density was explored. The 1-MCP distribution in commercial cool stores, under room cooling condition, was uniform irrespective of room shape. Rooms filled with fruit in wooden bins deplete 25 % more of the active substance than rooms filled with fruit in plastic bins. The calculated dose increases linearly with the amount of fruit in the cool store (filling density). Hence, this study suggests that dose prescription based on filling density is feasible.

CFD modeling using heterogeneous reaction kinetics for catalytic dehydrogenation syngas reactions in a fixed-bed reactor

A comprehensive 2D computational fluid dynamics (CFD) model was developed to simulate the flow behavior and catalytic dehydrogenation reaction of syngas in a heterogenous fixed-bed reactor (FBR). The model combined the porous medium CFD model with a reaction kinetics model. To acquire an accurate reaction kinetics model, a comprehensive reaction mechanism was studied for the heterogeneous catalytic dehydrogenation reaction of syngas over a supported metal catalyst. Based on the reaction mechanism and a statistical test, a reliable kinetics model was proposed. The CFD model combined with the above kinetics model was validated with one set of experimental data. The CFD model was also used to predict key reaction variable distributions such as the temperature and the component concentrations in the reactor.

Development and Validation of a Porous-Medium Computational Fluid Dynamics Model for a Fast Boron Shutdown System

The fast boron shutdown injection system in the CNA II pressurized heavy water reactor consists of a set of jets flowing through a very large moderator tank that contains an array of cylindrical coolant channels. The prediction of the turbulent jet mixing is required to determine an accurate distribution of boron inside the moderator tank. The boron distribution is used to calculate the multidimensional insertion of negative reactivity into the reactor during fast shutdown in a PARCS/RELAP5 model of CNA II.A computational fluid dynamics (CFD) code is used to determine the distribution of boron in the moderator tank. The flow is analyzed with a porous-medium model based on volume-averaged momentum, turbulent kinetic energy, and turbulence dissipation equations. The additional source terms that arise due to the averaging must be constituted. The constitutive relations for the additional source terms that are implemented in the present model are (a) the drag force on an array of cylinders for the momentum equations and (b) the additional mixing effect of the cylinders, which results in the sources of turbulent kinetic energy and turbulence dissipation transport equations.The CFD analysis is performed on a porous, axisymmetric domain. The CFD results are compared with data for the boron concentration distribution obtained in a scaled geometrically similar experiment, demonstrating the validity of the approach. Finally, based on the similarity of turbulent jets, the validated model is scaled up to prototypic conditions and inserted into the PARCS/RELAP5 model.