Search Results (1,541)

The method of extracting energy from a fluid environment using flapping foils offers advantages such as structural simplicity and environmental friendliness. However, its low energy harvesting efficiency remains a significant factor limiting its development. This study employs suction and blower-based control (SBC) to enhance the energy harvesting efficiency of flapping foils. Using an orthogonal experimental design and numerical methods, 49 representative combinations of SBC geometries were selected for numerical simulation. The effects and priority rankings of geometric parameters on foil performance were statistically analyzed. It was found that under the optimal geometry (the suction slot position is 0.54c, the injection slot position is 0.79c, the width of the slot is 0.015c, the angle of the suction slot is −3°, and the angle of the injection slot is −9°), the energy harvesting efficiency can reach 40.7%. Furthermore, under laminar flow conditions, the benefit of SBC increases with higher Reynolds numbers (Re). At Re = 2200, SBC maximized the improvement in energy harvesting efficiency by 76%. No significant correlation was observed between the flapping amplitude and the SBC effect. However, the reduced frequency significantly influences the efficiency improvement generated by SBC. The SBC method shifts the foil’s optimal operating region towards lower reduced frequencies, which benefits energy harvesting efficiency. The research presented herein may have potential applications in the development of marine energy systems and bio-inspired propulsion. Full article

Accurate micro gas flow measurement is critical for medical ventilator calibration, environmental gas monitoring, and semiconductor manufacturing. Laminar flowmeters are widely employed in micro gas flow measurement applications owing to their inherent advantages of high linearity, the absence of moving components, and a broad measurement range. Nevertheless, due to the low measurement accuracy under micro gas flow caused by nonlinear errors and a relatively complex structure, traditional laminar flow measurement devices exhibit limitations in micro gas flow measurement scenarios. This study proposes a novel micro gas flow measurement method based on a single capillary laminar flow element, which simplifies the structure and enhances applicability in the field of micro gas flow. Through structural optimization with precise control of the capillary length–diameter ratios and theoretical error correction based on computational analysis, nonlinear errors were effectively reduced while improving the measurement accuracy in the field of micro gas flow. The proposed methodology was systematically validated through computational fluid dynamics simulations (ANSYS Fluent 2021 R1) and experimental investigations using a dedicated test platform. The experimental results show that the relative error of the measurement system within the full measurement range is less than ±0.6% (1–10 cm³/min; cm³/min means cubic centimeter per minute), and its accuracy is superior to 1% of reading (1% Rd) or 1.5% of reading (1.5% Rd) of conventional laminar flowmeters. The fitting curve of the flow rate versus the pressure difference derived from the measurement results maintains an excellent linear correlation (R² > 0.99), thus confirming that this method has practical application value in the field of micro gas flow measurement. Full article

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

Straw fiber curtain contains a plant fiber blanket woven from crop straw, which is mainly used to protect embankment slopes from rainwater erosion. To investigate the erosion control performance of slopes covered with straw fiber curtains of different structural configurations, physical model tests were conducted in a 95 cm × 65 cm × 50 cm (length × height × width) test box with a slope ratio of 1:1.5 under controlled artificial rainfall conditions (20 mm/h, 40 mm/h, and 60 mm/h). The study evaluated the runoff characteristics, sediment yield, and key hydrodynamic parameters of slopes under the coverage of different straw fiber curtain types. The results show that the A-type straw fiber curtain (woven with strips of straw fiber) has the best effect on water retention and sediment reduction, while the B-type straw fiber curtain (woven with thicker straw strips) with vertical straw fiber has a better effect regarding water retention and sediment reduction than the B-type transverse straw fiber curtain. The flow of rainwater on a slope covered with straw fiber curtain is mainly a laminar flow. Straw fiber curtain can promote the conversion of water flow from rapids to slow flow. The Darcy-Weisbach resistance coefficient of straw fiber curtain increases at different degrees with an increase in rainfall time. Full article

This study presents a detailed analysis of the combustion dynamics of stoichiometric H₂–air and CH₄–air mixtures in a 20 L closed vessel over an initial temperature range of 298–423 K. We integrate experimental pressure–time P(t) measurements with numerical analysis to extract laminar burning velocity (LBV) and deflagration index (K_G) values, and we assess three independent kinetic mechanisms (KiBo_MU, University of San Diego, Lund University) via simulations. For H₂–air, LBV increases from 0.50 m/s at 298 K to 0.94 m/s at 423 K (temperature exponent α ≈ 1.79), while for CH₄–air, LBV rises from 0.36 m/s to 0.96 m/s (α ≈ 2.82). In contrast, the deflagration index K_G decreases by ca. 20% for H₂–air and ca. 30% for CH₄–air over the same temperature span. The maximum explosion pressure (P_max) and peak pressure rise rate ((dP/dt)_max) also exhibit systematic increases with temperature. A comparison with model predictions shows agreement within experiments, providing data for safety modeling and kinetic mechanism validation in H₂- and CH₄-based energy systems. Full article

The converter transformer is subjected to AC/DC composite voltage during operation, and the sealed and time-varying internal state makes its electric field distribution and charge accumulation unable to be monitored in real-time experiments. In this paper, aiming at the influence of bubbles in the oil passage of the converter transformer on charge accumulation before discharge, a simulation model in a laminar flow environment is established, and four different calculation conditions are set to simulate the charge accumulation in 1 s. It is found that under laminar flow conditions, the trapped bubbles on the insulation paper wall play an obvious role in intensifying the charge accumulation in transformer oil, and the extreme range of charge density will increase by about 10⁴ times. Bubbles aggravate the electric field distortion, and the insulation strength of bubbles is lower, which becomes the weak link of insulation. In the laminar flow environment, the oil flow will take away part of the accumulated charge in the oil, but in the case of trapped bubbles, the charge accumulation in the insulating paper will increase from the order of 10⁻² to 10⁻¹. In the case of no bubbles, the transformer oil layer flow will increase the charge accumulation in the insulation paper by 4–5 orders of magnitude. Therefore, it can be seen that the flow of transformer oil will increase the deterioration level of insulation paper. And when the transformer oil is already in the laminar flow state, the influence of laminar flow velocity on charge accumulation is not obvious. The research results in this paper provide a time-varying simulation reference state for the charge accumulation problem that cannot be measured experimentally under normal charged operation conditions, and we obtain quantitative numerical results, which can provide a valuable reference for the study of transformer operation and insulation discharge characteristics. Full article

Microchannel heat sinks (MCHSs) have emerged as an alternative for dissipating high heat rates. However, manufacturing MCHSs can be expensive, so exploring low-cost additive manufacturing using 3D printing is warranted. Before fabrication, the entropy minimization method helps to optimize MCHSs, enhancing their cooling capacity while maintaining their power consumption. We employed this method through computational simulation of laminar water flow in rectangular microchannels ($\mathsf{\mu }$C) and minichannels (mC), considering two heat fluxes (10 and 50 kW/m²). The results showed that the frictional entropy is only appreciable in the smallest and largest channels. These computational results enabled the fabrication of the optimal $\mathsf{\mu }$C and mC, whose experimental implementation validated the computational findings. Moreover, we computationally studied the effect of using rGO-Ag water-based nanofluids as a coolant. In general, a reduction in total entropy generation was observed at a heat flux of 50 kW/m². Although at lower heat flux (10 kW/m²), mC was the best option. Channels with lower heights were more effective at higher heat fluxes (≥50 kW/m²). Our findings offer a cost-effective strategy for fabricating high-performance cooling systems while also highlighting the interplay among heat flux, entropy generation, and nanofluid-enhanced cooling. Full article

The numerical modelling of the melt flow in Si crystal growth plays an important role for improving the resistivity distribution of crystals grown in industrial processes. However, recent series of experiments have shown that the existing numerical model—a finite volume solver with incompressible laminar approximation of the melt flow—is not always accurate enough to describe the experimental results for 4″ crystals. To improve the simulation results, material properties have been revised. For some of them, such as the Marangoni or thermal expansion coefficients, the literature suggests different values varying by more than a factor of two. Therefore, simulations using different combinations of parameters were run to perform parameter calibration. The study demonstrated that the description of induced heat on the open melting front needs to be modified to obtain the shape of phase boundaries that provides the best agreement to the experiment. It was concluded that new values should be assigned to several material properties in the model, most importantly the Marangoni coefficient $M=-1.2·{10}^{-4}{\displaystyle \frac{\mathrm{N}}{\mathrm{m}·\mathrm{K}}}$, and that an appropriate turbulence model may help to describe the dopant transport more precisely. Full article

Sustainable aviation fuels (SAFs) are vitally important for aviation decarbonization. The laminar burning velocity (LBV), a key parameter reflecting the combustion behavior of fuel/oxidizer mixtures, serves as a fundamental metric for evaluating SAF performance. This paper systematically reviews and evaluates the LBV experiment method and the performance of traditional aviation fuel, SAFs produced via different pathways, and individual components (n-alkanes, iso-alkanes, cycloalkanes, and aromatic hydrocarbons, as well as the impacts of isomers and homologues) in aviation fuels. It is found that LBV values of different SAFs exhibit significant fluctuations, approaching or slightly deviating from those of conventional aviation fuels. Carbon number, branching degree, substituent types, and testing methods in the components all affect LBV performance. Specifically, increased branching in iso-alkanes reduces LBV, cyclohexane and benzene show higher LBV than their methylated counterparts (methylcyclohexane and toluene), and n-alkylcyclohexanes/benzenes with short (C1–C3) side chains demonstrate minimal LBV variation. Spherical flame methods yield more consistent (and generally lower) LBV values than stagnation flame techniques. These findings provide insights for optimizing SAF–conventional fuel blends and enhancing drop-in compatibility while ensuring operational safety and usability. Full article

Improving photovoltaic (PV) panel performance under extreme climatic conditions is critical for advancing sustainable energy systems. In hyper-arid regions, elevated operating temperatures significantly reduce panel efficiency. This study investigates and compares three cooling techniques—air cooling, water cooling, and porous media cooling—using thermal and electrical modeling based on CFD simulations in ANSYS. The numerical model replicates a PV system operating under peak solar irradiance (900 W/m²) and realistic ambient conditions in Adrar, Algeria. Simulation results show that air cooling leads to a modest temperature reduction of 6 °C and a marginal efficiency gain of 0.25%. Water cooling, employing a top-down laminar flow, reduces cell temperature by over 35 °C and improves net electrical output by 30.9%, despite pump energy consumption. Porous media cooling, leveraging passive evaporation through gravel, decreases panel temperature by around 30 °C and achieves a net output gain of 26.3%. Mesh sensitivity and validation against experimental data support the accuracy of the model. These findings highlight the significant potential of water and porous material cooling strategies to enhance PV performance in hyper-arid environments. The study also demonstrates that porous media can deliver high thermal effectiveness with minimal energy input, making it a suitable low-cost option for off-grid applications. Future work will integrate long-term climate data, real diffuser geometries, and experimental validation to further refine these models. Full article

This study investigates the application of deep learning (DL) techniques for predicting temperature fields in the SM1 swirl-stabilized turbulent non-premixed flame. Two distinct DL approaches were developed using a comprehensive CFD database generated via the steady laminar flamelet model coupled with the SST k-ω turbulence model. The first approach employs a fully connected dense neural network to directly map scalar input parameters—fuel velocity, swirl ratio, and equivalence ratio—to high-resolution temperature contour images. In addition, a comparison was made with different deep learning networks, namely Res-Net, EfficientNetB0, and Inception Net V3, to better understand the performance of the model. In the first approach, the results of the Inception V3 model and the developed Dense Model were found to be better than Res-Net and Efficient Net. At the same time, file sizes and usability were examined. The second framework employs a U-Net-based convolutional neural network enhanced by an RGB Fusion preprocessing technique, which integrates multiple scalar fields from non-reacting (cold flow) conditions into composite images, significantly improving spatial feature extraction. The training and validation processes for both models were conducted using 80% of the CFD data for training and 20% for testing, which helped assess their ability to generalize new input conditions. In the secondary approach, similar to the first approach, studies were conducted with different deep learning models, namely Res-Net, Efficient Net, and Inception Net, to evaluate model performance. The U-Net model, which is well developed, stands out with its low error and small file size. The dense network is appropriate for direct parametric analyses, while the image-based U-Net model provides a rapid and scalable option to utilize the cold flow CFD images. This framework can be further refined in future research to estimate more flow factors and tested against experimental measurements for enhanced applicability. Full article

This study presents a numerical comparison between Direct numerical simulation (DNS) and the standard κ-ε turbulence model to evaluate natural convection in a two-dimensional, differentially heated, air-filled cavity over the Rayleigh number range 10³ to 10¹⁰. The objective is to assess the predictive capabilities of both methods across laminar and turbulent regimes, with a particular emphasis on the quantitative comparison of thermal characteristics under high Rayleigh number conditions. The Navier–Stokes and energy equations were solved using the finite element method with Boussinesq approximation, employing refined meshes near the hot and cold walls to resolve thermal and velocity boundary layers. The results indicate that for Ra ≤ 10⁶, the κ-ε model significantly underestimates temperature gradients, maximum velocities, and average Nusselt numbers, with errors up to 19.39%, due to isotropic assumptions and empirical formulation. DNS, in contrast, achieves global energy balance errors of less than 0.0018% across the entire range. As Ra increases, the κ-ε model predictions converge to DNS, with Nusselt number deviations dropping below 1.2% at Ra = 10¹⁰. Streamlines, temperature profiles, and velocity distributions confirm that DNS captures flow dynamics more accurately, particularly near the wall vortices. These findings validate DNS as a reference solution for high-Ra natural convection and establish benchmark data for assessing turbulence models in confined geometries Full article

Presented in this work is a harmonic balance (HB)-based pseudo-time code-coupling approach applied to a one-degree-of-freedom vortex-induced vibration (VIV) problem of a circular cylinder in a low-Reynolds-number laminar flow regime. Unlike physical time coupling used in traditional time-accurate methods, this novel approach updates both of the fluid and structure fields by integrating respective HB forms of governing equations in pseudo-time, and then couples the two fields in pseudo-time using a partitioned approach. A separate procedure is adopted to determine the VIV frequency at every code-coupling iteration, which enables the simultaneous convergence of variables of both fields in a single run of the solver. For the cases considered here, lock-in vibrations are predicted over a range of Reynolds numbers, inside and outside the resonant range. The results are verified by a time-accurate method and also validated against earlier experimental data, demonstrating the efficiency and robustness of the pseudo-time code-coupling approach. Full article

In recent times, fiber reinforced polymer composite materials have become more popular due to their remarkable features such as high specific strength, high stiffness and durability. Particularly, Carbon Fiber Reinforced Polymer (CFRP) composites are one of the most prominent materials used in the field of transportation and building engineering, replacing conventional materials due to their attractive properties as mentioned. In this work, a CFRP laminate is fabricated with carbon fiber mats and epoxy by a hand layup technique. Alumina (Al₂O₃) micro particles are used as a filler material, mixed with epoxy at different weight fractions of 0% to 4% during the fabrication of CFRP laminates. The important objective of the study is to investigate the influence of alumina micro particles on the mechanical performance of the laminates through characterization for various physical and mechanical properties. It is revealed from the results of study that the mass density of the laminates steadily increased with the quantity of alumina micro particles added and subsequently, the porosity of the laminates is reduced significantly. The SEM micrograph confirmed the constituents of the laminate and uniform distribution of Al₂O₃ micro particles with no significant agglomeration. The hardness of the CFRP laminates increased significantly for about 60% with an increase in weight % of Al₂O₃ from 0% to 4%, whereas the water gain % gradually drops from 0 to 2%, after which a substantial rise is observed for 3 to 4%. The improved interlocking due to the addition of filler material reduced the voids in the interfaces and thereby resist the absorption of water and in turn reduced the plasticity of the resin too. Tensile, flexural and inter-laminar shear strengths of the CFRP laminate were improved appreciably with the addition of alumina particles through extended grain boundary and enhanced interfacial bonding between the fibers, epoxy and alumina particles, except at 1 and 3 wt.% of Al₂O₃, which may be due to the pooling of alumina particles within the matrix. Inclusion of hard alumina particles resulted in a significant drop in impact strength due to appreciable reduction in softness of the core region of the laminates. Full article

Increasing water scarcity in arid regions has prompted the mining industry to develop strategies to maximize water recovery and reuse, especially in tailings treatment processes. In this context, the present investigation evaluated the effects of sodium polyacrylate (NaPA) on the compressibility and viscoelasticity of clayey tailings in the presence of hard water containing calcium and magnesium. To this end, clayey slurries were analyzed using rheological tests (rheograms and oscillatory viscoelasticity), zeta potential measurements, and compressibility tests using batch centrifugation. The yield stress was determined using the Herschel–Bulkley model, while the compressive yield stress (Py(Φ)) was calculated as a key indicator to characterize the degree of sediment consolidation. The results showed that NaPA, due to its anionic nature and high degree of ionization at pH 8, induces effective particle dispersion by increasing electrostatic repulsion and decreasing the interaction force between particles, which reduces both rheological parameters and compressive yield stress. For the 70/30 quartz/kaolin mixture, the yield stress decreased from 70.54 to 61.64 Pa in CaCl₂ and from 57.51 to 52.95 Pa in MgCl₂ in the presence of NaPA. It was also observed that suspensions in the presence of magnesium ions presented greater compressibility than those with calcium, attributable to the greater hydration radius of magnesium (10.8 Å), which favors less dense and more easily deformable network structures. Furthermore, a higher proportion of kaolin in the mixture resulted in higher yield stresses, a product of the clay’s laminar structure, colloidal size, and high surface area, both in the absence and presence of NaPA. Overall, the results show that incorporating NaPA significantly improves the compressibility and rheology of clayey tailings in hard water, offering a promising alternative for optimizing water recovery and improving tailings management efficiency in the context of water restrictions. Full article