Search Results (603)

The synthesis of “green ammonia” from “green hydrogen” represents a critical pathway for renewable energy integration and industrial decarbonization. This study investigates the green ammonia synthesis process using an axial–radial fixed-bed reactor equipped with three catalyst layers. A simplified two-dimensional physical model was developed, and a multiscale simulation approach combining computational fluid dynamics (CFD) with physics-informed neural networks (PINNs) employed. The simulation results demonstrate that the majority of fluid flows axially through the catalyst beds, leading to significantly higher temperatures in the upper bed regions. The reactor exhibits excellent heat exchange performance, ensuring effective preheating of the feed gas. High-pressure zones are concentrated near the top and bottom gas outlets, while the ammonia mole fraction approaches 100% near the bottom outlet, confirming superior conversion efficiency. By integrating PINNs, the prediction accuracy was substantially improved, with flow field errors in the catalyst beds below 4.5% and ammonia concentration prediction accuracy above 97.2%. Key reaction kinetic parameters (pre-exponential factor k₀ and activation energy Ea) were successfully inverted with errors within 7%, while computational efficiency increased by 200 times compared to traditional CFD. The proposed CFD–PINN integrated framework provides a high-fidelity and computationally efficient simulation tool for green ammonia reactor design, particularly suitable for scenarios with fluctuating hydrogen supply. The reactor design reduces energy per unit ammonia and improves conversion efficiency. Its radial flow configuration enhances operational stability by damping feed fluctuations, thereby accelerating green hydrogen adoption. By reducing fossil fuel dependence, it promotes industrial decarbonization. Full article

A computational fluid dynamics (CFD) numerical simulation methodology was implemented to model transient heating processes in steel industry reheating furnaces, targeting combustion efficiency optimization and carbon emission reduction. The effects of oxygen concentration (O₂%) and different fuel types on the flow and heat transfer characteristics were investigated under both oxygen-enriched combustion and MILD oxy-fuel combustion. The results indicate that MILD oxy-fuel combustion promotes flue gas entrainment via high-velocity oxygen jets, leading to a substantial improvement in the uniformity of the furnace temperature field. The effect is most obvious at O₂% = 31%. MILD oxy-fuel combustion significantly reduces NOx emissions, achieving levels that are one to two orders of magnitude lower than those under oxygen-enriched combustion. Under MILD conditions, the oxygen mass fraction in flue gas remains below 0.001 when O₂% ≤ 81%, indicating effective dilution. In contrast, oxygen-enriched combustion leads to a sharp rise in flame temperature with an increasing oxygen concentration, resulting in a significant increase in NOx emissions. Elevating the oxygen concentration enhances both thermal efficiency and the energy-saving rate for both combustion modes; however, the rate of improvement diminishes when O₂% exceeds 51%. Based on these findings, MILD oxy-fuel combustion using mixed gas or natural gas is recommended for reheating furnaces operating at O₂% = 51–71%, while coke oven gas is not. Full article

The steady plane radial diverging flow of a viscous or inviscid particle-fluid suspension is studied using a novel two-fluid model. For the initial flow field with a uniform particle distribution, our results show that the relative velocity of particles with respect to the fluid depends on their inlet velocity ratio at the entrance, the mass density ratio and the Stokes number of particles, and the particles heavier (or lighter) than the fluid will move faster (or slower) than the fluid when their inlet velocities are equal (then Stokes drag vanishes at the entrance). The relative motion of particles with respect to the fluid leads to particle migration and the non-uniform distribution of particles. An explicit expression is obtained for the steady particle distribution eventually attained due to particle migration. Our results demonstrated and confirmed that, for both light particles (gas bubbles) and heavy particles, depending on the particle-to-fluid mass density ratio, the volume fraction of particles attains its maximum or minimum value near the entrance of the radial flow and after then monotonically decreases or increases with the radial coordinate and converges to an asymptotic value determined by the particle-to-fluid inlet velocity ratio. Explicit solutions given here could help quantify the steady particle distribution in the decelerating radial flow of a particle-fluid suspension. Full article

Resin Transfer Molding (RTM) is a widely used composite manufacturing process where liquid resin is injected into a closed mold filled with a fibrous preform. By applying this process, large pieces with complex shapes can be produced on an industrial scale, presenting excellent properties and quality. A true physical phenomenon occurring in the RTM process, especially when using vegetable fibers, is related to the absorption of resin by the fiber during the infiltration process. The real effect is related to the slowdown in the advance of the fluid flow front, increasing the mold filling time. This phenomenon is little explored in the literature, especially for non-isothermal conditions. In this sense, this paper does a numerical study of the liquid injection process in a closed and heated mold. The proposed mathematical modeling considers the radial, three-dimensional, and transient flow, variable injection pressure, and fluid viscosity, including the effect of liquid fluid absorption by the reinforcement (fiber). Simulations were carried out using Computational Fluid Dynamic tools. The numerical results of the filling time were compared with experimental results, and a good approximation was obtained. Further, the pressure, temperature, velocity, and volumetric fraction fields, as well as the transient history of the fluid front position and injection fluid volumetric flow rate, are presented and analyzed. Full article

In tight sandstone gas reservoirs, proppant flowback severely limits stable gas production. This study uses laboratory flowback experiments and field analyses of the ShaXimiao tight sandstone in the Wenxing gas area to investigate the mechanisms controlling sand production. The experiments show that displacing fluid viscosity significantly affects the critical sand-flow velocity: with high-viscous slickwater (5 mPa·s), the critical velocity is 66% lower than with low-viscous formation water (1.15 mPa·s). The critical velocity for coated proppant is three times that of the mixed quartz sand and coated proppant. If the confining pressure is maintained, but the flow rate is further increased after the proppant flowback, a second instance of sand production can be observed. X-ray diffraction (XRD) tests were conducted for sand produced from practical wells to help find the sand production reasons. Based on experimental and field data analysis, sand production in Well X-1 primarily results from proppant detachment during rapid shut-in/open cycling operations, while in Well X-2, it originates from proppant crushing. The risk of formation sand production is low for both wells (the volumetric fraction of calcite tested from the produced sands is smaller than 0.5%). These findings highlight the importance of fluid viscosity, proppant consolidation, and pressure management in controlling sand production. Full article

For a significant fluid model and the truncated M-fractional (1 + 1)-dimensional nonlinear generalized water wave equation, distinct types of truncated M-fractional wave solitons are obtained. Ocean waves, tidal waves, weather simulations, river and irrigation flows, tsunami predictions, and more are all explained by this model. We use the improved $(G^{\prime }/G)$ expansion technique and a modified extended direct algebraic technique to obtain these solutions. Results for trigonometry, hyperbolic, and rational functions are obtained. The impact of the fractional-order derivative is also covered. We use Mathematica software to verify our findings. Furthermore, we use contour graphs in two and three dimensions to illustrate some wave solitons that are obtained. The results obtained have applications in ocean engineering, fluid dynamics, and other fields. The stability analysis of the considered equation is also performed. Moreover, the stationary solutions of the concerning equation are studied through modulation instability. Furthermore, the used methods are useful for other nonlinear fractional partial differential equations in different areas of applied science and engineering. Full article

In water-scarce regions such as Jordan, accurate tracking of water flows is critical for informed water management. This study applied the Water Accounting Plus (WA+) framework using open-source remote sensing data from the FAO WaPOR portal to develop agricultural water accounting (AWA) for the Amman–Zarqa Basin (AZB) during 2014–2022. Inflows, outflows, and water consumption were quantified using WaPOR and other open datasets. The results showed a strong correlation between WaPOR precipitation (P) and rainfall station data, while comparisons with other remote sensing sources were weaker. WaPOR evapotranspiration (ET) values were generally lower than those from alternative datasets. To improve classification accuracy, a correction of the WaPOR-derived land cover map was performed. The revised map achieved a producer’s accuracy of 15.9% and a user’s accuracy of 86.6% for irrigated areas. Additionally, ET values over irrigated zones were adjusted, resulting in a fivefold improvement in estimates. These corrections significantly enhanced the reliability of key AWA indicators such as basin closure, ET fraction, and managed fraction. The findings demonstrate that the accuracy of P and ET data strongly affects AWA outputs, particularly the estimation of percolation and beneficial water use. Therefore, calibrating remote sensing data is essential to ensure reliable water accounting, especially in agricultural settings where data uncertainty can lead to misleading conclusions. This study recommends the use of open-source datasets such as WaPOR—combined with field validation and calibration—to improve agricultural water resource assessments and support decision making at basin and national levels. 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

Splashed droplets in the vacuum chamber play an important role in decarburization and degassing in Ruhrstahl–Heraeus (RH), but the scholars do not pay attention to the behaviors of splashed droplets. Thus, it is necessary to propose a new method to investigate the splashed droplets. A Euler–Euler model and the inter-phase momentum transfer are applied to investigate the interaction between the molten steel and the bubbles, and the gas domain in the vacuum chamber is included in the computational domain in order to describe the movement of the splashed droplets. Numerical results show that the flow field predicted by Euler–Euler model agrees well with the experimental data. There is a higher gas volume fraction near the up-snorkel wall, the “fountain” formed by the upward flow from the up-snorkel exceeds 0.1 m above the free surface, and the center of the vortex between the upward stream and the downward stream is closer to the upward stream in the vacuum chamber. Full article

The production of AISI 304 stainless steel (a corrosion-resistant alloy prone to solidification defects from high alloy content) particularly benefits from twin-roll strip casting—a short-process green technology enabling sub-rapid solidification (the maximum cooling rate exceeds 1000 °C/s) control for high-performance steels. However, the internal phenomena within its molten pool remain exceptionally challenging to monitor. This study developed a multiscale numerical model to simulate coupled fluid flow, heat transfer, and solidification in AISI 304 stainless steel twin-roll strip casting. A quarter-symmetry 3D model captured macroscopic transport phenomena, while a slice model resolved mesoscopic solidification structure. Laboratory experiments had verified that the deviation between the predicted temperature field and the measured average value (1384.3 °C) was less than 5%, and the error between the solidification structure simulation and the electron backscatter diffraction (EBSD) data was within 5%. The flow field and flow trajectory showed obvious recirculation zones: the center area was mainly composed of large recirculation zones, and many small recirculation zones appeared at the edges. Parameter studies showed that, compared with the high superheat (110 °C), the low superheat (30 °C) increased the total solid fraction by 63% (from 8.3% to 13.6%) and increased the distance between the kiss point and the bottom of the molten pool by 154% (from 6.2 to 15.8 mm). The location of the kiss point is a key industrial indicator for assessing solidification integrity and the risk of strip fracture. In terms of mesoscopic solidification structure, low superheat promoted the formation of coarse columnar crystals (equiaxed crystals accounted for 8.9%), while high superheat promoted the formation of equiaxed nucleation (26.5%). The model can be used to assist in the setting of process parameters and process optimization for twin-roll strip casting. Full article

Digitalization is leading the development direction of oilfields in the future. And the precise measurement of produced fluids is the core component supporting the construction of digital oilfields. To mitigate the adverse effects of liquid carryover from gas wells on metering devices at the wellhead, this paper proposed a compact tandem-type gas–liquid separator structure (CTGLS) based on the principle of cyclone separation. The internal flow field characteristics and separation performance of the gas–liquid separator were analyzed through numerical simulation and experimental methods. The influence of various liquid concentrations, inlet flow rates, and overflow split ratios on the velocity field, medium distribution, and separation efficiency of gas–liquid separators was obtained. The optimal regulatory relationship of the underflow split ratio under different operating parameters was elucidated. The results indicate that, as the liquid concentration increases, the axial velocity changes significantly within the underflow region of the secondary separator, while the liquid volume fraction in the cyclone chamber increases gradually. Increasing the inlet flow rate and the split ratio can enhance the axial velocity at the overflow outlet, but it will reduce the liquid phase separation efficiency. The mathematical model correlating the operating parameters with the separation efficiency was established using the response surface method. And the best operation regulation mechanism of the split ratio was obtained under different inlet flow rates and liquid concentrations. Full article

This study presents a comprehensive numerical investigation into the influence of blade profile geometry on the internal flow dynamics and hydraulic performance of Cross-Flow Turbines (CFTs) under varying runner speeds. Four blade configurations, flat, round, sharp, and aerodynamic, were systematically evaluated using steady-state, two-dimensional Computational Fluid Dynamics (CFD) simulations. The Shear Stress Transport (SST) k–ω turbulence model was employed to resolve the flow separation, recirculation, and turbulence across both energy conversion stages of the turbine. The simulations were performed across runner speeds ranging from 270 to 940 rpm under a constant head of 10 m. The performance metrics, including the torque, hydraulic efficiency, water volume fraction, pressure distribution, and velocity field characteristics, were analyzed in detail. The aerodynamic blade consistently outperformed the other geometries, achieving a peak efficiency of 83.5% at 800 rpm, with improved flow attachment, reduced vortex shedding, and lower exit pressure. Sharp blades also demonstrated competitive efficiency within a narrower optimal speed range. In contrast, the flat and round blades exhibited higher turbulence and recirculation, particularly at off-optimal speeds. The results underscore the pivotal role of blade edge geometry in enhancing energy recovery, suppressing flow instabilities, and optimizing the stage-wise performance in CFTs. These findings offer valuable insights for the design of high-efficiency, site-adapted turbines suitable for micro-hydropower applications. Full article

In fractional routing, the flows are distributed through different paths; this allows the maximum efficiency to be achieved by using several partial capacities to balance flow. However, the mathematical formalism for dynamic and scalable implementation is yet to be developed. This paper proposes the aforementioned hybrid framework of edge-linear transformations, AIs, and QCs for fractional routing optimizations. The system encodes flows by means of vector linear transformations over finite fields, supports real-time reconfiguration via deep reinforcement learning, and employs quantum algorithms such as QAOA and HHL for efficient minimization of path costs. The Python 3-based implementations of the model were utilized to test DAGs of a small- and medium-scale, showing a 30% increase in computational efficiency and a 25% drop in runtime compared to classical implementations. The evidence states that the practical-scalability results can be used for the real-time applications of emerging IoT and 6G networks. Full article

Rapid mixing is widely prevalent in the field of microfluidics, encompassing applications such as biomedical diagnostics, drug delivery, chemical synthesis, and enzyme reactions. Mixing efficiency profoundly impacts the overall performance of these devices. However, at the micro-scale, the flow typically presents as laminar flow due to low Reynolds numbers, rendering rapid mixing challenging. Leveraging the vortices within a droplet of the Taylor flow and inducing chaotic convection within the droplet through serpentine channels can significantly enhance mixing efficiency. Based on this premise, we have developed a droplet micromixer that integrates the T-shaped channels required for generating Taylor flow and the serpentine channels required for inducing chaotic convection within the droplet. We determined the range of inlet liquid flow rate and gas pressure required to generate Taylor flow and conducted experimental investigations to examine the influence of the inlet conditions on droplet length, total flow rate, and mixing efficiency. Under conditions where channel dimensions and liquid flow rates are identical, Taylor flow achieves a nine-fold improvement in mixing efficiency compared to single-phase flow. At low Reynolds number (0.57 ≤ Re ≤ 1.05), the chip can achieve a 95% mixing efficiency within a 2 cm distance in just 0.5–0.8 s. The mixer proposed in this study offers the advantages of simplicity in manufacturing and ease of integration. It can be readily integrated into Lab-on-a-Chip devices to perform critical functions, including microfluidic switches, formation of nanocomposites, synthesis of oxides and adducts, velocity measurement, and supercritical fluid fractionation. Full article

To explore the impact of the aspect ratio of the channels in the flow fields of solid oxide electrolysis cells on the performance of the cell, we developed three-dimensional models for cells with varying aspect ratios. Our findings revealed that channels with low and high aspect ratios exhibit higher maximum pressure drops, whereas those with medium aspect ratios have the lowest pressure drops. Additionally, the mole fraction of the hydrogen decreases as the channel’s aspect ratio increases. We also computed the polarization curves for SOEC operating under three distinct aspect ratio channels. Our results suggest that structures with low aspect ratios exhibit the poorest electrochemical performance, suitable only for brief operations at low current densities; medium aspect ratio structures exhibit a balanced performance, making them suitable for various operating conditions; and high aspect ratio structures are best suited for operations at high current densities. This study on selecting different aspect ratios aids in determining the optimal channel parameters for different operating conditions, ultimately enhancing the performance of solid oxide electrolysis cells. Full article