Pure Fluids Research Articles

Oscillatory squeeze flow through an Oldroyd-B fluid-saturated porous layer

This study deals with the analytical investigation of oscillatory squeeze film flow through a Brinkman viscoelastic Oldroyd-B fluid-saturated porous layer subject to two vertically harmonically oscillatory disks. The validity of the present proposed analytical solutions is first demonstrated for the Newtonian fluids when both Λ1 and Λ2 tend to zero by comparison with the previous literature. Results demonstrate that an increase in the elasticity parameter Λ1 correlates with a rise in axial velocities, indicating that the relaxation time Λ1 facilitates enhanced squeeze flow. In the case of squeeze film flow in porous layers, low oscillating frequencies exert minimal effects on axial velocities, independent of variations in the viscoelasticity parameter Λ1. However, at higher oscillating frequencies, axial velocities escalate with increasing the viscoelasticity parameter Λ1. Furthermore, the retardation time Λ2 of the viscoelastic fluid shows no significant effect on the axial velocity, regardless of oscillating frequency changes in both pure fluids and porous layers.

Frozen Patterns in Viscoelastic Droplets Impacting on a Subcooled Surface.

The impact of droplets on a cold surface is ubiquitous in nature and various industrial applications, ranging from the icing of supercooled droplets on aircraft to the solidification of ink droplets in 3D printing. However, our understanding of the impact dynamics of droplets of complex fluids on cold surfaces is still very limited. Here, we experimentally study the spreading and frozen patterns of viscoelastic polymer droplets falling onto a subcooled substrate. We observe that the maximum spreading diameter of post-impact droplets decreases with increasing the subcooling temperature and the polymer concentration. Remarkably, all experimental data for spreading collapse into a universal curve, following the classic theory that accounts for inertial, capillary, and viscous forces. Unexpectedly, we find that, in contrast to the case of pure fluids, which exhibits three frozen modes, only two distinct modes, namely, freezing and hierarchical cracking, can be observed for polymer droplets. Finally, based on the undercooling temperature and polymer concentration, we construct a phase diagram for characterizing the morphologies of all frozen patterns. We expect that our findings may have implications in understanding the solidification of complex fluids on cold surfaces, for instance, in the fields of spray coating, inkjet printing, and additive manufacturing.

A Review of the Homogenized Lattice Boltzmann Method for Particulate Flow Simulations: From Fundamentals to Applications

The homogenized lattice Boltzmann method (HLBM) has emerged as a flexible computational framework for studying particulate flows, providing a monolithic approach to modeling pure fluid flows and flows through porous media, including moving solid and porous particles, within a unified framework. This paper presents a thorough review of HLBM, elucidating its underlying principles and highlighting its diverse applications to particle-laden flows in various fields as reported in literature. These include studies leading to new fundamental knowledge on the settling of single arbitrarily shaped particles as well as application-oriented research on wall-flow filters, hindered settling, and evaluation of the damage potential during particle transport. Among the strengths of HLBM are its monolithic approach, which allows seamless simulation of different fluid-solid interactions, and its ability to handle arbitrary particle shapes, including irregular and concave geometries, while resolving surface interactions to capture local forces. In addition, its parallel scheme based on the lattice Boltzmann method (LBM) results in high computational efficiency, making it suitable for large-scale simulations, even though LBM requires small time steps. Important future development needs are identified, including the addition of a lubrication force correction model, performance enhancements, such as support for hybrid parallelization and GPU, and the extension of compatible contact models to accommodate concave shapes. These advances promise expanded capabilities for HLBM and broader applicability for solving complex real-world problems.

Linking Thermal Conductivity to Equations of State Using the Residual Entropy Scaling Theory.

In recent years, the application of the residual entropy scaling (RES) method for modeling transport properties has become increasingly prominent. Based on Yang et al. (Ind. Eng. Chem. Res. 2021, 60, 13052) in modeling the thermal conductivity of refrigerants, we present here an RES model that extends Yang et al.'s approach to a wider range of pure fluids and their mixtures. All fluids available in the REFPROP 10.0 software, i.e., those with reference equations of state (EoS), were studied. A total of 71,554 experimental data of 125 pure fluids and 16,702 experimental data of 164 mixtures were collected from approximately 647 references, mainly based on the NIST ThermoData Engine (TDE) database 10.1. As a result, over 68.2% (corresponding to the standard deviation of a normal distribution) of the well-screened experimental data agree with the developed RES model within 3.1% and 4.6% for pure fluids and mixtures, respectively. Comparative analysis against the various models implemented in the REFPROP 10.0 (one of the state-of-the-art software packages for thermophysical property calculations) reveals that our RES model demonstrates analogous statistical agreement with experimental data yet with much fewer parameters. Regarding the average absolute value of the relative deviation (AARD) from experimental values to model predictions, the developed RES model shows a smaller or equal AARD for 74 pure fluids out of 125 and 76 mixtures out of 164. Besides, a detailed examination of the impact of the critical enhancement term on mixture calculations was conducted. To use our model easily, a software package written in Python is provided in the Supporting Information.

Heat transfer in a non-uniformly heated enclosure filled by NEPCM water nanofluid

Purpose This paper aims to focuses on by investigate the heat transmission and free convective flow of a suspension of nano encapsulated phase change materials (NEPCMs) within an enclosure. Particles of NEPCM have a core-shell structure, with phase change material (PCM) serving as the core. Design/methodology/approach The enclosure consists of a square chamber with an insulated wall on top and bottom and vertical walls that are differently heated. The governing equations are investigated using the finite element technique. A grid inspection and validation test are done to confirm the precision of the results. Findings The effects of fusion temperature (varying from 0.1 to 0.9), Stefan number (changing from 0.2 to 0.7), Rayleigh number (varying from 103 to 106) and volume fraction of NEPCM nanoparticles (changing from 0 to 0.05) on the streamlines, isotherms, heat capacity ratio and average Nusselt number are investigated using graphs and tables. From this investigation, it is found that using a NEPCM nano suspension results in a significant enhancement in heat transfer compared to pure fluid. This augmentation becomes more important for the low Stefan number, which is around 16.57% approximately at 0.2. Secondary recirculation is formed near the upper left corner as a result of non-uniform heating of the left vertical border. This eddy expands notably as the Rayleigh number rises. The study findings indicate that the NEPCM nanosuspension has the potential to act as a smart working fluid, significantly enhancing average Nusselt numbers in enclosed chambers. Research limitations/implications The NEPCM particle consists of a core (n-octadecane, a phase-change material) and a shell (PMMA, an encapsulation material). The host fluid water and the NEPCM particles are considered to form a dilute suspension. Practical implications Using NEPCMs in energy storage thermal systems show potential for improving heat transfer efficiency in several engineering applications. NEPCMs merge the beneficial characteristics of PCMs with the enhanced thermal conductivity of nanoparticles, providing a flexible alternative for effective thermal energy storage and control. Originality/value This paper aims to explore the free convective flow and heat transmission of NEPCM water-type nanofluid in a square chamber with an insulated top boundary, a uniformly heated bottom boundary, a cooled right boundary and a non-uniformly heated left boundary.

Little-Cost Potentiometric and Spectrophotometric Procedures for Cephalothin Assessment in Pure and Biological Fluids.

Low-cost potentiometric and spectrophotometric procedures for cephalothin (CPI) determination in pure and biological fluids were investigated. The potentiometric technique is created through titration of CPI with an aqueous medium of 0.1 M NaOH at an ionic strength of μ = 0.3 M sodium chloride and room temperature by a combined glass pH electrode. Using the standard addition method, we found that the detection and quantitative limits were 0.042 mg/mL, with the standard deviation SD = 0.011, correlation coefficient R = 0.9880 (n = 5), and linear concentration ranges from 0.042 to 0.82 mg/mL. This technique was utilized to assess CPI in pure solutions, urine, and serum with suitable results. No interference was exposed in the presence of public components of the samples under study. Recovery of CPI for pure and biological fluids is in the range of 98.2-101%. Also, the spectrophotometric method has been performed through the formation of the Prussian Blue (PB) complex. The reaction between the acidic hydrolysis product of CPI (T = 60 °C) and the mixture of Fe3+ with hexacyanoferrate (III) ions (HCF(III)) was detected for the spectrophotometric determination of the drug. The maximum absorbance of the formed complex was measured at λ = 283 nm with 2.0 × 103 L mol-1 cm-1 molar absorptivity. Reaction states have been advanced to acquire the PB complex of great sensitivity and longer stability. In optimal states, the absorbent of the PB compound was attained to grow linearly with the increase in the concentration of CPI, which agrees with the correlation coefficient values. The detection and quantitative limits were 0.000036 and 0.0012 mg/mL, respectively, with the standard deviation, SD = 0.0005, correlation coefficient, R = 0.9955 (n = 5), and the linearity range of the calibration plot 0.0005-0.02 mg/mL CPI. The planned technique was positively utilized for the detection of CPI in both urine and serum models. The results fit well with the data found from the potentiometric method.

Thermal management and power generation characteristics in a bifurcating channel by using a piezo-embedded inclined elastic fin assembly during turbulent forced convection of ternary nanofluid

Numerous engineering systems use piezoelectric energy harvesters (PE-EHs), which have several benefits including low cost, simplicity, better power density, and ease of installation. They can be used in different applications for energy harvesting and different external sources such as wind and vortex induced vibrations due to fluid–structure interaction can be utilized. This study uses a unique elastic fin PE/EH assembly for power generation, thermal management, and flow control in a bifurcating channel. Performance of the system is improved by using ternary nanofluid in the channel cooling system. Galerkin weighted residual FEM with ALE is used as the solution method. The convective heat transfer performance and power generation by the EH device are investigated in relation to the varying following parameters: Reynolds number (Re between 10000 and 30000), PE-EH inclination (γ between 0 and 60), fin horizontal location (xf between −H and H), and nanoparticle loading in the base fluid (ϕ between 0 and 0.03). The vortex size and distribution near the junction are significantly influenced by the fin inclination and horizontal location of the fin assembly within the bifurcating channel. When varying other parameters of interest, using nanofluid at the highest loading results in significant deflection of the fin assembly and power generation within the PE-EH. Enhancement factors (EFs) for power generation becomes 15.6 and 39.8 when cases of lowest and highest Re are compared with pure fluid and nanofluid while they are 2.93 and 3.38 for thermal performance improvements. Fin inclination of γ=30 is found as the optimum inclination for achieving the highest power from the assembly. Higher inclination of elastic fin/PE-EH assembly results in cooling performance deterioration while average Nu reduces by a factor of 2.94 by varying inclination from γ=30 to γ=60 with nanofluid. For power generation, effects of using nanofluid with varying inclination is significant and EF becomes 252 from γ=0 to γ=30. There are opposing tendencies for the device’s power generation and cooling performance enhancement when the fin’s horizontal placement is changed. EF for average Nu is 7.25 for varying fin location. As the loading of nanoparticle inside the base fluid increases, the average Nu and generated power exhibit non-linear rising characteristics. Polynomial type correlations are provided for the average Nu and power from the device by varying elastic fin assembly inclination and nanoparticle solid volume fraction. Potential of using hybrid nanofluid in PE-EH embedded thermo-fluid system is shown. The design, development, and optimization of self-sufficient power production systems that may be used to various thermo-fluid systems, such as electronic cooling and thermal control in a range of heat transfer devices, may benefit from the findings.

Non-similar approach for enhanced heat and mass transfer in nanofluid using Keller box algorithm

The nanofluids provide various benefits over pure fluids in heat and mass transport applications; hence, their research is crucial. For instance, they can increase heat transfer rate by enhancing the fluid’s thermal conductivity and may enhance mass transfer rate by changing the surface characteristics. Furthermore, nanofluids are being demonstrated to effectively diminish pressure drops in exchangers for heat, which can lower energy consumption and operating expenses. In the existing literature, the majority of the theoretical studies considered self-similar flows. However, there are certain actual flow situations that do not allow for a self-similar solution. The current study considers such of those situations where the non-similarity of the transport phenomena is unavoidable. The non-similarity of the present problem is caused by the consideration of thermophoretic diffusion or the contribution of viscous dissipation when the wall temperature follows a power-law form. For a pure fluid, the same problem admits a self-similar solution in the absence of viscous dissipation effects. In this problem, the non-similarity is caused by the nature of the thermal transport process and not because of the momentum transport. Therefore, the consideration of viscous dissipation in the boundary layer of nanofluid is an interesting aspect to explore the behavior of thermal and mass transport phenomena. Moreover, the current analysis intends to investigate the transport enhancement in a non-similar flow of a nanofluid by utilizing the Buongiorno model. In the current nonsimilar modeling, possibilities for the existence of a self-similar solution are also highlighted. An implicit finite-difference numerical scheme, the Keller-Box method, is utilized. The problem involves several physical parameters of interest, such as the Eckert number, Lewis number, Brownian motion parameter, and thermophoresis parameter, whose potential impact on the non-similar nature of the problem and on thermal enhancement is analyzed and quantified.

Experimental Study on the Effect of Skin Friction Drag and Convective Heat Transfer for Viscoelastic and Pseudoplastic Fluid Flow

Drag Reducing Agents (DRAs) have a huge impact and major concern in engineering and industrial applications. It makes the fluid flow turbulent to laminar, dampens eddy reduces head loss by up to a certain limit, and saves pumping energy costs. Viscosity is the property that dampens eddy due to the viscous effect, which increases the fluidity up to a certain limit. Pseudoplasticity is the shear thinning effect that decreases viscosity when the flow rate increases. So, for the viscoelastic effect, we can increase the concentration up to a certain limit to reduce head loss. Still, during flow due to the pseudoplastic effect, the viscosity will start decreasing which is a negative effect. So, these combined effects are studied to reduce skin friction drag in the pipeline and save energy costs which will be convenient for the food industry, chemical, and medicine industries. In this investigation, investigation is carried out for 0.3 g/L, 0.2 g/L, and 0.15 g/L of xanthan gum in turbulent flow to observe the pressure drop and heat transfer rate. The study reveals that after increasing viscosity the pressure drop reduced significantly. Conversely, the heat transfer rate was also reduced due to the poor mixing effect. A higher performance and less vibration of the pump was also observed. It was concluded that the frictional pressure drop was reduced up to 85 % and the heat transfer rate was reduced by up to 90% by increasing the concentration of the DRA up to 0.3 g/L at 10 LPM than the pure water or base fluid as a working substance on the double pipe heat exchanger. As the heat transfer rate reduced up to 90% with reducing pressure drop another aim of the study was to establish a concentration and flowrate for which the heat transfer rate is maximum and it was found at a concentration of 0.15 g/L of DRAs (drag reducing agents) at 22 LPM (maximum flowrate at this setup).

Optimal mixture design for organic Rankine cycle using machine learning algorithm

This study presents a new design tool for working fluid mixtures in organic Rankine cycles. The proposed tool comprises a blend model for the thermophysical properties of the formulated mixtures, an ORC modelto predict the performance of the mixtures in a specific application, and an optimizer based on the Bayesian inference method to identify the optimal mixtures compositions to be assessed. The tool is programmed to optimize an objective function based on predefined optimization targets. Importantly, the targets and their respective weights within the objective function can be adjusted to meet the specific requirements of the application under analysis, making this approach adaptable to diverse research and industrial objectives. The algorithm is applied to a case study to demonstrate its ability to define a low-GWP blend that can replace HFC-134a in a micro-scale ORC with recuperator, while maintaining and potentially enhancing performance. The optimization targets specified for the case study are the net power output, the net efficiency, the GWP and the blend size. Power and efficiency are computed through a validated model of the low-temperature ORC system used as benchmark case. The results showed that the procedure was able to formulate several blends that comply with the targets of the assigned task. Amongst the high-scoring mixtures, the most used pure fluids are R32, R152a, R1234yf, and R1234ze(E). The presence of HCs is limited to fewer mixtures, playing the main role of GWP-limiter. A method to estimate the flammability classification of the blends has been also applied, obtaining that most of them belong to the ASHRAE class 2l, except when an HC is present, in which case the fluid is may result in class 3.

Particle Dynamics Study on Influencing Factors of Ice Slurry Flow Characteristics in District Cooling Systems

In district cooling systems, substituting the conventional cooling medium with ice slurry represents an ideal approach to achieve economical operation. During pipeline transportation, ice slurry exhibits heterogeneous flow characteristics distinct from those of pure fluids. Consequently, investigating the flow field characteristics of non-homogeneous ice slurry, quantitatively analyzing the rheological variations and flow resistance laws due to the uneven distribution of ice particles, and standardizing the comprehension and depiction of flow patterns within ice slurry pipes hold significant theoretical importance and practical value. This study analyzes the heterogeneous isothermal flow characteristics of ice slurry in a straight pipe by employing particle dynamics and the Euler–Euler dual-fluid model. Taking into account the impact of ice particles’ non-uniform distribution on the rheological properties of ice slurry, a particle concentration diffusion equation is incorporated to develop an isothermal flow resistance model for ice slurry. The flow behavior of ice slurry with initial average ice particle fractions (IPFs) ranging from 0% to 20% in DN20 horizontal straight and elbow pipes is examined. The findings reveal that the degree of heterogeneous flow in ice slurry is inversely proportional to the initial velocity and directly proportional to the initial concentration of ice particles. When the flow velocity is close to 0.5 m/s, the flow resistance of ice particles exhibits a linear positive correlation with changes in flow velocity, whereas the flow resistance of the fluid-carrying phase displays a linear negative correlation. As the flow rate increases to 1 m/s, the contribution of each phase to the total flow resistance becomes independent of the initial velocity parameter. Additionally, the drag fraction of the ice particle phase is positively associated with the initial concentration of ice particles. Furthermore, the phenomenon of “secondary flow” arises when ice slurry flows through an elbow, enhancing the mixing of ice particles with the carrier fluid. The extent of this mixing intensifies with a decrease in the turning radius and an increase in the initial velocity.

Optimizing solar collector through constructal design of Y-shaped networks with power-law nanofluid flow

Solar energy is a plentiful and renewable resource; therefore, its use through clean energy technologies is necessary to reduce the consumption of fossil fuels and their consequent impact on the environment. Solar thermal energy can be harnessed to collect thermal energy through solar collectors for domestic or industrial use. In this work, a Y-shaped duct network was developed for a solar collector with a disc-shaped body. The shape and size of the network were defined using the constructal design method to harvest greater thermal energy from exposure to irradiance. For this purpose, the working fluid was a nanofluid composed of nanoparticles and a base fluid with non-Newtonian behavior, as described by the power-law model. The properties of the nanofluid were described using theoretical models that depend on the volume fraction of the nanoparticles in the base fluid. The aspect ratio of each element in the network was defined under the condition of minimum thermal resistance. For the shear-thinning nanofluid with a volume fraction of 0.04, the thermal resistance was reduced by 5.5% with an aspect ratio 5.8% lower than that of the pure base fluid. The minimum thermal resistance of the Y-shaped network arrangement occurs for shear-thinning fluids, whereas thermal resistance increases for shear-thickening fluids. This effect can be observed at different levels of branching and in pumping power. Results show that increasing the volume fraction of the nanofluid and base fluid with shear-thinning behavior aids in achieving minimal thermal resistance more easily with a smaller network. The above offers new design options for devices optimized to improve solar harvesting and thermal management, through shape, structure and rheological characteristics.

Aerodynamic breakup of emulsion droplets in airflow

AbstractAerodynamic breakup refers to the process where large droplets are fragmented into small droplets by the aerodynamic force in airflow, which plays a vital role in fluid atomization and spray applications. Previous research has primarily concentrated on the aerodynamic breakup of single‐component droplets, but investigations into the breakup of emulsion droplets are limited. This study experimentally investigated the aerodynamic breakup of water‐in‐oil emulsions in airflow, utilizing high‐speed photography to observe the breakup process and digital in‐line holography to measure fragment sizes. Comparative analyses between emulsion droplets and single‐component droplets are conducted to examine the breakup morphology, breakup regime, deformation characteristics, and fragment size distributions. The emulsion droplets exhibit higher apparent viscosity and shorter stretching lengths of the bag film and peripheral rim due to the presence of a dispersed phase. The breakup regime transitions of emulsions are modeled by integrating the viscosity model of emulsions and the transition model of the pure fluid. The fragment sizes of emulsion droplets are larger due to the shorter lengths of the bag film and peripheral rim.

Exploring Natural Convection and Entropy Generation in a Closed Water Tank Utilizing Nanofluid: a Computational Study

Theoretical framework: This study presents a comprehensive investigation into three-dimensional natural convection within a confined cavity filled with an alumina-water nanofluid. Objective: Utilizing numerical simulations, we explore the influence of nanoparticles' volume fraction and Rayleigh number () on entropy generation, heat transfer efficiency, and fluid behavior within the water tank. Method: The study delves into the conservation equations governing mass, momentum, and energy within the context of three-dimensional laminar natural convection. It focuses on steady, incompressible flow, employing the Boussinesq approximation to account for variations in fluid density due to temperature gradients. Results and conclusion: Our findings indicate that increasing Rayleigh numbers lead to heightened entropy generation, with values ranging from to, primarily driven by intensified buoyant flow. However, the presence of nanoparticles significantly mitigates entropy generation, enhancing the overall thermal performance of the system. Moreover, nanofluids demonstrate superior heat transfer capabilities compared to pure fluids, with higher nanoparticle concentrations resulting in increased heat transfer rates, ranging from to alumina. Research implications: As a result of such thorough research, qualitative examinations of velocity fields and entropy generation patterns further highlight the role of nanofluids in improving heat transfer efficiency while reducing irreversible processes within the cavity.

Innovative molecular descriptors in QSPR modeling: Integrating Carnahan-Starling EoS for predicting diffusion coefficients in hydrocarbons and mixtures

The rapid and accurate prediction of self-diffusion coefficients for pure fluids and mutual diffusion coefficients for binary mixtures remains a focal point of current research. In this work, molecular descriptors are innovatively defined by introducing molecular repulsive and attractive pressures based on the Carnahan-Starling equation of state. This approach aims to improve the quantitative structure–property relationship (QSPR) models for predicting thermophysical properties that vary with thermodynamic conditions. The shapely additive explanation method is employed for a comprehensive analysis of the model mechanism. Among the six molecular descriptors selected, our defined attractive pressure (patt), MATS2e and SpMin3_Bh(v) contribute significantly to the self-diffusion coefficient QSPR model. Based on this approach, QSPR models are constructed for 15 hydrocarbons and five of their binary mixtures. The results demonstrate that the GA-BPNN-based QSPR model for pure fluids achieves high prediction accuracy, with an external Rext2 of 0.978 and an external RMSEext of 5.349 × 10−9·m2·s−1. The optimal mixture descriptor type is x1d1+x2d2, and the GS-SVM-based mixture QSPR model predicts 98.24 % of values within a 5 % error margin, with Rext2 of 0.991 and RMSEext of 0.042 × 10−9·m2·s−1.

Modeling the thermodynamic properties of cyclic alcohols with the SAFT-γ Mie approach: application to cyclohexanol and menthol systems

Cyclic alcohols are commonly found in natural and synthetic products and are involved in many biological processes. An ability to model their thermodynamic properties is of interest in food, flavouring, and pharmaceutical manufacturing, particularly for mixtures for which available experimental data are limited. Good examples are mixtures including menthol, a naturally occurring cyclic alcohol widely used in the food and pharmaceutical industries, well-known for its cooling-sensation properties and its role in the discovery of the TRPM8 receptor. Here, we extend the SAFT-γ Mie group-contribution method to model cyclic alcohols, by introducing a new cCHOH group (c for cyclic) composed of two identical Mie segments. Three association sites (two electronic sites of type e and one hydrogen site of type H) are also included to mediate hydrogen bonding. New parameters that characterise the group interactions (one new like interaction and 26 new unlike interactions) are developed and are employed to determine the thermophysical properties (vapour pressure, saturation density, vaporisation enthalpy, and second-order thermodynamic derivative properties) of pure cyclic alcohols, and mixture properties (vapour–liquid equilibria, liquid–liquid equilibria, solid–liquid equilibria, density, and excess enthalpy) of cyclic alcohols in several solvents. The quality of the model is evaluated by comparing predictive calculations with experimental data of 76 systems: six pure fluids and 70 binary mixtures, selected from a large range of solvent families: cyclic, linear, and branched alkanes, 1-alcohols, 2-alcohols, 2-ketones, esters, aromatic compounds, water, and carbon dioxide. Very good overall agreement is found, including for the prediction of solid–liquid solubility, which confirms the transferability of the new group parameters. Together with previously developed parameters, these open the way for the prediction of the thermodynamic properties of further complex mixtures.

Hemodynamics in the treatment of pseudoaneurysm caused by extreme constriction of aortic arch with coated stent.

To evaluate the changes in distal vascular morphology and hemodynamics in patients with extremely severe aortic coarctation (CoA) after covered palliative (CP) stent dilation with different surgical strategies. Perioperative computed tomography angiography and digital subtraction angiography were utilized to construct three aortic models with varying stenosis rates and one follow-up model in a patient with extremely severe CoA. The models included: an idealized non-stenosed model (A: 0%), a model post initial stent deployment (B: 28%), a model post balloon expansion (C: 39%), and a model 18 months after post-balloon expansion (D: 39%). Consistent boundary conditions were applied to all models, and hemodynamic simulation was conducted using the pure fluid method. The narrowest and distal diameter of the stent increased by 34.71% and 59.29%, respectively, from model B to C. Additionally, the distal diameter of the stent increased by -13.80% and +43.68% compared to the descending aorta diameter, respectively. Furthermore, the ellipticity of the maximum cross-section of the aneurysm region in model A to D continued to increase. The oscillatory shear index at the stenosis to the region of the aneurysm were found to be higher in Models A and B, and lower in Models C and D. At the moment of maximum flow velocity, the blood flow distribution in models A and B was more uniform in the widest section of the blood vessels at the distal end of the stenosis, whereas models C and D exhibited disturbed blood flow with more than 2 eddy currents. The time-averaged wall shear stress (TAWSS) decreased in the distal and basal aneurysms, while it significantly increased at the step position. The aneurysmal region exhibited an endothelial cell activation potential value lower than 0.4 Pa-1. In patients with extremely severe CoA, it is crucial to ensure that the expanded diameter at both ends of the CP stent does not exceed the native vascular diameter during deployment. Our simulation results demonstrate that overdilation leads to a decrease in the TAWSS above the injured vessel, creating an abnormal hemodynamic environment that may contribute to the development and enlargement of false aneurysms in the early postoperative period. ClinicalTrials.gov, (NCT02917980).

Corrigendum to: “Revisiting the Entropy-Scaling Concept for Shear-Viscosity Estimation from Cubic and SAFT Equation of State: Application to Pure Fluids in Gas, Liquid and Supercritical States”

Corrigendum to: “Revisiting the Entropy-Scaling Concept for Shear-Viscosity Estimation from Cubic and SAFT Equation of State: Application to Pure Fluids in Gas, Liquid and Supercritical States”

An unconditionally stable scheme for the immersed boundary method with application in cardiac mechanics

The stability of the immersed boundary (IB) method is a challenge in simulating fluid–structure interaction problems, where time step constraints are significantly stricter than in pure fluid simulations. We propose a novel unconditionally stable scheme for the immersed boundary finite element (IBFE) method. The structure is handled implicitly and characterized by strain energy functions, rather than being modeled as fibers or membranes. Through energy estimate, we prove the unconditional stability of the fully discrete approximation in the absence of the convective term. In real simulations of cardiac mechanics problems, the time step is much larger, only limited by the Courant–Friedrichs–Lewy condition of the fluid. The novelty of this work lies in the combination of dual interpolation and distribution operators, the Jacobian-free Newton–Krylov method for solving nonlinear algebraic systems, and the semi-Lagrangian method for handling the convective term. To validate the effectiveness and accuracy of our approach, we present various benchmarks and conduct a quasi-static simulation of a three-dimensional real left ventricular model. We have shown that the numerical stability of our scheme is very robust even with much larger time step compared to conventional explicit IB methods. Our work paves the way for further works on efficient solvers of the IBFE method.

Particle-based modeling and GPU-accelerated simulation of cellular blood flow

Computational modeling and simulation of cellular blood flow is highly desired for understanding blood microcirculation and blood-related diseases such as thrombosis and tumor, but it remains a challenging task primarily because blood in microvessels should be described as a dense suspension of different types of deformable cells. The focus of the present work is on the development of a particle-based and GPU-accelerated numerical method that is able to quickly simulate the various behaviors of deformable cells in three-dimensional arbitrarily complex geometries. We employ a two-fluid model to describe blood flow, incorporating the deformation and aggregation of cells. A smoothed dissipative particle dynamics is used to solve the two-fluid model, and a discrete microstructure model is applied for the cell deformation, as well as a Morse potential model for the cell aggregation. The heterogeneous CPU-GPU environment is established, where each GPU thread is dedicated to a particle, and the CPU is mainly responsible for loading and exporting data. Five test cases are conducted against analytical theory, experimental data, and previous numerical results, for pure fluid, cell deformation, cell aggregation, cell suspension and the cellular flow in a complex network, respectively. It is shown that the methodology can accurately predict various behaviors of cells, and the GPU is well suited for particle-based modeling. Especially for cellular blood flow, where calculating cellular forces is a compute-intensive and time-consuming task, the GPU offers exceptional parallel capabilities, significantly enhancing the simulation efficiency. The speedup is about 3.5 times faster than the CPU parallelization with 96 cores for the pure fluid, and this acceleration nearly reaches 20 times when cells are included in the simulations. Particularly, the calculations for deformation and aggregation forces demonstrate a substantial speedup, achieving the improvements of up to 120 and 640 times, respectively, compared to their serial counterparts. The present methodology can effectively integrate various behaviors of cells, and has the potential in simulating very large microvascular networks at organ levels.