Search Results (726)

This study applies Computational Fluid Dynamics (CFD) and mathematical modeling to examine uterine and umbilical arterial blood flow during pregnancy, providing a more detailed understanding of hemodynamic changes across gestation. Statistical analysis of Doppler ultrasound data from a large cohort of more than 200 pregnant women (in the second and third trimesters) reveals significant increases in the umbilical arterial peak systolic velocity ($PSV$) between the 22nd and 30th weeks, while uterine artery velocities remain relatively stable, suggesting adaptations in vascular resistance during pregnancy. By combining the Navier–Stokes equations with Doppler ultrasound-derived inlet velocity profiles, we quantify several key fluid dynamics parameters, including time-averaged wall shear stress ($TAWSS$), oscillatory shear index ($OSI$), relative residence time ($RRT$), Reynolds number ($Re$), and Dean number ($De$), evaluating laminar flow stability in the uterine artery and secondary flow patterns in the umbilical artery. Since blood exhibits shear-dependent viscosity and complex rheological behavior, modeling it as a non-Newtonian fluid is essential to accurately capture pulsatile flow dynamics and wall shear stresses in these vessels. Unlike conventional imaging techniques, CFD offers enhanced visualization of blood flow characteristics such as streamlines, velocity distributions, and instantaneous particle motion, providing insights that are not easily captured by Doppler ultrasound alone. Specifically, CFD reveals secondary flow patterns in the umbilical artery, which interact with the primary flow, a phenomenon that is challenging to observe with ultrasound. These findings refine existing hemodynamic models, provide population-specific reference values for clinical assessments, and improve our understanding of the relationship between umbilical arterial flow dynamics and fetal growth restriction, with important implications for maternal and fetal health monitoring. Full article

This paper addresses the critical gap in the existing literature regarding the combined buoyancy–Marangoni convection of power-law fluids in three-dimensional porous media with complex evaporation surfaces. Previous studies have rarely investigated the convective heat transfer mechanisms in such systems, and there is a lack of effective methods to accurately track fractal evaporation surfaces, which are ubiquitous in natural and engineering porous media (e.g., geological formations, industrial heat exchangers). This research is significant because understanding heat transfer in these complex porous media is essential for optimizing energy systems, enhancing thermal management in industrial processes, and improving the efficiency of phase-change-based technologies. For this scientific issue, a general model is designed. There is a significant temperature difference on the left and right sides of the model, which drives the internal fluid movement through the temperature difference. The upper end of the model is designed as a complex evaporation surface, and there is flowing steam above it, thus forming a coupled flow field. The VOF fractal reconstruction method is adopted to approximate the shape of the complex evaporation surface, which is a major highlight of this study. Different from previous research, this method can more accurately reflect the flow and phase change on the upper surface of the porous medium. Through numerical simulation, the influence of the evaporation coefficient on the flow and heat transfer rate can be determined. Key findings from numerical simulations reveal the following: (1) Heat transfer rates decrease with increasing fractal dimension (surface complexity) and evaporation coefficient; (2) As the thermal Rayleigh number increases, the influence of the Marangoni number on heat transfer diminishes; (3) The coupling of buoyancy and Marangoni effects in porous media with complex evaporation surfaces significantly alters flow and heat transfer patterns compared to smooth-surfaced porous media. This study provides a robust numerical framework for analyzing non-Newtonian fluid convection in complex porous media, offering insights into optimizing thermal systems involving phase changes and irregular surfaces. The findings contribute to advancing heat transfer theory and have practical implications for industries such as energy storage, chemical engineering, and environmental remediation. Full article

This paper explores the complex dynamics of mixed convective flow in a Casson fluid saturated in a non-Darcy porous medium, focusing on the influence of gyrotactic microorganisms, internal heat generation, and multiple convective mechanisms. Casson fluids, known for their non-Newtonian behavior, are relevant in various industrial and biological contexts where traditional fluid models are insufficient. This study addresses the limitations of the standard Darcy’s law by examining non-Darcy flow, which accounts for nonlinear inertial effects in porous media. The governing equations, derived from conservation laws, are transformed into a system of no linear ordinary differential equations (ODEs) using similarity transformations. These ODEs are solved numerically using a finite differencing method that incorporates central differencing, tridiagonal matrix manipulation, and iterative procedures to ensure accuracy across various convective regimes. The reliability of this method is confirmed through validation with the MATLAB (R2024b) bvp4c scheme. The investigation analyzes the impact of key parameters (such as the Casson fluid parameter, Darcy number, Biot numbers, and heat generation) on velocity, temperature, and microorganism concentration profiles. This study reveals that the Casson fluid parameter significantly improves the velocity, concentration, and motile microorganism profiles while decreasing the temperature profile. Additionally, the Biot number is shown to considerably increase the concentration and dispersion of motile microorganisms, as well as the heat transfer rate. The findings provide valuable insights into non-Newtonian fluid behavior in porous environments, with applications in bioengineering, environmental remediation, and energy systems, such as bioreactor design and geothermal energy extraction. Full article

Protein-polyphenol-based delivery vehicles are effective strategies for encapsulating bioactive compounds, thereby enhancing their solubility and bioaccessibility. In this study, dihydromyricetin/soy protein isolate (DHM/SPI) complexes were used as emulsifiers to prepare Pickering emulsions for DHM delivery. The results show that DHM and SPI form negatively charged complexes through hydrogen bonding, and the complex size decreases and stabilizes with increasing DHM addition. The size of the emulsion droplets was inversely related to the concentration of DHM addition (c), particle concentration (w), and ionic strength (i). Conversely, the increasing oil phase concentration (φ) was positively correlated with droplet size. The CLSM results confirmed the expected oil-in-water emulsion, while the rheological behavior of the Pickering emulsion highlighted its elastic, gel-like network structure and non-Newtonian fluid properties. Moreover, DHM effectively slowed lipid oxidation in the emulsion, and the bioaccessibility of DHM reached 33.51 ± 0.31% after in vitro simulated digestion. In conclusion, this emulsion system shows promising potential for delivering DHM and harnessing its bioactive effects. Full article

Understanding the rheological properties of fresh cement slurries is essential to maintain optimal pumpability, achieve dependable zonal isolation, and preserve long-term well integrity in oil and gas cementing operations and the 3D printing cement and concrete industry. However, accurately and efficiently modeling the rheological behavior of cement slurries remains challenging due to the complex fluid properties of fresh cement slurries, which exhibit non-Newtonian and thixotropic behavior. Traditional numerical solvers typically require mesh generation and intensive computation, making them less practical for data-scarce, high-dimensional problems. In this study, a physics-informed neural network (PINN)-based framework is developed to solve the governing equations of steady-state cement slurry flow in a tilted channel. The slurry is modeled as a non-Newtonian fluid with viscosity dependent on both the shear rate and particle volume fraction. The PINN-based approach incorporates physical laws into the loss function, offering mesh-free solutions with strong generalization ability. The results show that PINNs accurately capture the trend of velocity and volume fraction profiles under varying material and flow parameters. Compared to conventional solvers, the PINN solution offers a more efficient and flexible alternative for modeling complex rheological behavior in data-limited scenarios. These findings demonstrate the potential of PINNs as a robust tool for cement slurry rheological modeling, particularly in scenarios where traditional solvers are impractical. Future work will focus on enhancing model precision through hybrid learning strategies that incorporate labeled data, potentially enabling real-time predictive modeling for field applications. Full article

Concentrated suspensions exhibit intriguing behaviors under external forces, including vibration and shear. While previous studies have focused primarily on cornstarch suspensions, this paper reports a novel observation that colloidal silica suspensions also exhibit dancing, bouncing, solidification, and melting under vertical vibration. Unlike cornstarch, silica particles offer high stability, controlled size distribution, and tunable surface properties, making them an ideal system for investigating these phenomena. The 70 wt.% aqueous suspensions of spherical silica particles with a diameter of 0.55 μm were subjected to controlled vertical vibration (60–100 Hz, 100–500 m/s²). High-speed video analysis revealed dynamic transitions, including melting, fingering, squirming, fragmentation, and jumping. The solidified suspension retained its shape after vibration ceased but melted upon weak vibration. This study demonstrates that such dynamic state transitions are not exclusive to starch-based suspensions but can also occur in well-defined colloidal suspensions. Our findings provide a new platform for investigating shear-thickening, jamming, and vibrational solidification in suspensions with controllable parameters. Further work is required to elucidate the underlying mechanisms. Full article

The dam break flow problem consists of the phenomena where a fluid is suddenly released and is often used as a test case for multiphase flows numerical models or to analyze the underlying physics of complex free surface flows of both Newtonian and non-Newtonian fluids. Dam break flows of viscoplastic fluids (i.e., fluids that present a yield stress) are especially interesting for two reasons: many geological and industrial fluids can be characterized as viscoplastic fluids, and the yield stress represents a difficulty for numerical solutions. The viscoplastic fluids are simulated using the Bingham and Herschel–Bulkley models, and the results are compared with the flow development of power-law and Newtonian fluids (i.e., with no yield stress). This paper focuses on the numerical modeling of viscoplastic two-dimensional dam-break flows on an inclined bed as a means to analyze the shear stress field development over time and the formation of plug and pseudo-plug zones. It is shown that, for the very beginning of flow, the yield stress fluids were characterized by three distinctive shear stress zones, an occurrence that could not be found on the fluid with no yield stress. Full article

CO₂ displacement is a key technique that was examined through numerical methods in a 3D Hele–Shaw cell, with CO₂ as the displacing phase and shear-thinning fluids as the displaced phase. Without interfacial tension effects, the displacement shows branching patterns forming two vertically symmetric fingers, regardless of whether the displacing fluid is air or CO₂. Under CO₂ displacement, viscous fingering propagates farther and achieves higher displacement efficiency than air. Compared with air displacement, the finger advancing distance increases by 0.0035 m, and the displacement efficiency is 15.2% higher than that of air displacement. Shear-thinning behavior significantly influences the process; stronger shear thinning enhances interfacial stability and suppresses fingering. As the power-law index n increases (reducing shear thinning), the fingering length extends. Variations in interfacial tension reveal it notably affects fingering initiation and velocity in CO₂ displacement of non-Newtonian fluids, but has a weaker impact on fingering formation. Interfacial tension suppresses short-wavelength perturbations, critical to interface stability, jet breakup, and flows, informing applications like foam-assisted oil recovery and microfluidics. Full article

A hydrodynamic homogeneous model has been developed for the motion of mutually impenetrable viscoelastic non-Newtonian fluids taking into account surface tension forces. Based on this model, numerical simulations of cytokinesis hydrodynamics were performed. The cytoplasm is considered a non-Newtonian viscoelastic fluid. The model allows for the calculation of the formation and rupture of the intercellular bridge. Results from an analytical analysis shed light on the influence of the viscoelastic fluid’s relaxation time on cytokinesis dynamics. A comparison of numerical simulation results and experimental data showed satisfactory agreement. Full article

The electroosmotic flow (EOF) of non-Newtonian fluids plays a significant role in microfluidic systems. The EOF of Powell–Eyring fluid within a parallel-plate microchannel, under the influence of both electric field and pressure gradient, is investigated. Navier’s boundary condition is adopted. The velocity distribution’s approximate solution is derived via the homotopy perturbation technique (HPM). Optimized initial guesses enable accurate second-order approximations, dramatically lowering computational complexity. The numerical solution is acquired via the modified spectral local linearization method (SLLM), exhibiting both high accuracy and computational efficiency. Visualizations reveal how the pressure gradient/electric field, the electric double layer (EDL) width, and slip length affect velocity. The ratio of pressure gradient to electric field exhibits a nonlinear modulating effect on the velocity. The EDL is a nanoscale charge layer at solid–liquid interfaces. A thinner EDL thickness diminishes the slip flow phenomenon. The shear-thinning characteristics of the Powell–Eyring fluid are particularly pronounced in the central region under high pressure gradients and in the boundary layer region when wall slip is present. These findings establish a theoretical base for the development of microfluidic devices and the improvement of pharmaceutical carrier strategies. Full article

This study presents an innovative approach to quantifying uncertainty in Herschel–Bulkley (H-B) fluid flow through rectangular ducts, analyzing four scenarios: uncertain apparent viscosity (Case I), uncertain pressure gradient (Case II), uncertain boundary conditions (Case III) and uncertain apparent viscosity and pressure gradient (Case IV). Using the stochastic finite difference with homogeneous chaos (SFDHC) method, we produce probability density functions (PDFs) of fluid velocity with exceptional computational efficiency (243 times faster), matching the accuracy of Monte Carlo simulation (MCS). Key statistics and maximum velocity PDFs are tabulated and visualized for each case. Mean velocity shows minimal variation in Cases I, III, and IV, but maximum velocity fluctuates significantly in Case I (63.95–187.45% of mean), Case II (50.15–156.68%), and Case IV (63.70–185.53% of mean), vital for duct design and analysis. Examining the effects of different parameters, the SFDHC method’s rapid convergence reveals the fluid behavior index as the primary driver of maximum stochastic velocity, followed by aspect ratio and yield stress. These findings enhance applications in drilling fluid management, biomedical modeling (e.g., blood flow in vascular networks), and industrial processes involving non-Newtonian fluids, such as paints and slurries, providing a robust tool for advancing understanding and managing uncertainty in complex fluid dynamics. Full article

Gelatin is a commonly used protein-based hydrogel. However, the thermo-reversible nature of gelatin makes it unstable at physiological and higher temperatures. Therefore, this study adopted phosphates and glutaminase transaminase (TG) to modify gelation and studied the effects of combining sodium hexametaphosphate (SHP) and TG on the structure and gel properties of TG-crosslinked gelatin. This study focused on the effects of different SHP concentrations (0, 0.4, 0.8, 1.2, 1.6, 2.0, 2.4, 2.8 mmol/L) on the water distribution, textural properties, rheological properties, and microstructure of the TG-crosslinked gelatin gels. Results showed that the free water content in the TG-crosslinked gelatin gel declined with the increasing SHP addition when the concentration of SHP was kept below 2.0 mmol/L. The gel of TG-crosslinked gelatin at the SHP concentration of 1.6 mmol/L exhibited the highest hardness (304.258 g), chewiness (366.916 g) and η₅₀. All the TG-crosslinked gelatin gels with SHP modification were non-Newtonian pseudoplastic fluids. The G′ and G″ of TG-crosslinked gelatin increased before the SHP concentration reached 1.6 mmol/L, and the TG-crosslinked gelatin with 1.6 mmol/L SHP exhibited the largest G″ and G′. The fluorescence intensity of TG-crosslinked gelatin with SHP concentration above 1.6 mmol/L decreased with the increasing SHP concentration. SHP modified the secondary structure of TG-crosslinked gelatin gels. The gel of TG-crosslinked gelatin with the SHP concentration of 1.6 mmol/L exhibited a porous, smooth, and dense network structure. This research provides references for modifying gelatin and the application of gels in the encapsulation of bioactive ingredients and probiotics. Full article

The widespread use of mineral cutting fluids in metalworking poses challenges due to their poor wettability, toxicity, and non-biodegradability. This study explores cactus oil-based nanofluids as sustainable alternatives for metal cutting applications. Samples of cactus oil are prepared in plain form and with 0.025 wt.%, 0.05 wt.%, and 0.1 wt.% activated carbon nanoparticles (ACNPs) from recycled plastic waste. Plain cactus oil exhibited a 34% improvement in wettability over commercial soluble oil, further enhanced by 60% with 0.05 wt.% ACNPs. Cactus oil displayed consistent Newtonian behavior with a high viscosity index (283), outperforming mineral-based cutting fluid in thermal stability. The addition of ACNPs enhanced the dynamic viscosity by 108–130% across the temperature range of 40–100 °C. The presence of nano-additives reduced the friction coefficient in the boundary lubrication zone by a maximum reduction of 32% for CO2 compared to plain cactus oil. The physical and rheological results translated directly to the observed improvements in surface finish and tool wear during machining operations on H13 steel. Cactus oil with 0.05 wt.% ACNP outperformed conventional fluids, reducing surface roughness by 35% and flank wear by 57% compared to dry. This work establishes cactus oil-based nanofluids as a sustainable alternative, combining recycled waste-derived additives and non-edible feedstock for greener manufacturing. Full article

Fibrous biomaterials are essential in biomedical engineering, tissue engineering, and filtration due to their specific transport and mechanical properties. Fluid flow through these materials is critical for their function. However, many biological fluids exhibit non-Newtonian behavior, characterized by micro-rotational effects, which traditional models often overlook. The current study presents a machine learning (ML) framework for the prediction and understanding of hydraulic permeability in fibrous biomaterials with a micropolar fluid. A dataset of 1000 numerical simulations was generated by varying the micropolar fluid properties and the fiber volume fraction in a periodic porous structure with nine parallel cylindrical fibers in a square lattice. Six powerful ML algorithms were deployed: Decision Trees (DT), Random Forests (RF), XGBoost, LightGBM, Support Vector Regression (SVR), and k-Nearest Neighbors (kNN). The balance of predictive capacity to unseen data values (tracking $R^2$ values and error metrics) with computational efficiency for all algorithms was assessed. The best-performing ML algorithm was subsequently used to interpret the decisions made by the model using Shapley Additive exPlanations (SHAP) analysis and understand the role of feature importances. The SHAP findings highlight the potential of ML in capturing complex fluid interactions and guiding the design of advanced fibrous biomaterials with optimized hydraulic permeability. Full article

The influence of biopolymer–biopolymer chain interactions on selected rheological properties of aqueous solutions from konjac (KG), xanthan gum (XG), and carboxymethyl cellulose (CMC) was investigated using viscosity measurements in extensional and shear flow, as well as normal force ($F_N$) measurements generated in shear flow. It was found that a KG solution of 0.05% behaves as a Newtonian fluid. Other solutions of KG (0.1, 0.2%), XG, and CMC revealed a non-linear dependence of viscosity on the shear rate. The extensional viscosity dependence on the elongation rate was non-linear and indicated shear-thinning over the entire KG concentration range, with the lowest values noted at 0.05% (0.5–0.8 Pas) and the highest at 0.2% (1.0–1.3 Pas). Similar observations were obtained with 0.1% XG and CMC solutions. Analysis regarding the shear rate dependence of the $F_N$ showed that hysteresis was observed for all KG concentrations tested. Only for the 0.2% KG solution were the $F_N$ values negative over the entire range of shear rates estimated, as in the case of the XG and CMC solutions. The obtained time constants from the DeKee model indicate the dominance of elastic contributions for the XG and CMC solutions and viscous contributions for the CMC solutions in the case of an extensional flow. Full article