Search Results (9,788)

Background: Oxaliplatin-based hyperthermic intraperitoneal chemotherapy (HIPEC) using the original 30 min protocol has shown limited benefits in patients with peritoneal metastasis of colorectal cancer (PMCRC), likely due to the short duration, which limits drug penetration into tumor nodules. Bevacizumab, an antiangiogenic antibody that modifies the tumor microenvironment, may improve drug delivery during HIPEC. This in silico study evaluates the availability of oxaliplatin within tumor nodules when HIPEC is performed after bevacizumab treatment. Methods: Using a computational fluid dynamics (CFD) model of HIPEC, the temperature and oxaliplatin distribution within the rat abdomen were calculated, followed by a model of drug transport within tumor nodules located at various sites in the peritoneum. The vascular normalization effect of the bevacizumab treatment was incorporated by adjusting the biophysical parameters of the tumor nodules. The effective penetration depth values, including the thermal enhancement ratio of cytotoxicity, were then compared between HIPEC alone and HIPEC combined with the bevacizumab treatment. Results: After bevacizumab treatments at doses of 0.5 mg/kg and 5 mg/kg, the oxaliplatin availability increased by up to 20% and 45% when HIPEC was performed during the vascular normalization phase, with the penetration depth increasing by 1.5-fold and 2.3-fold, respectively. Tumors with lower collagen densities and larger vascular pore sizes showed higher oxaliplatin enhancement after the combined treatment. Bevacizumab also enabled a reduction in the oxaliplatin dose (up to half at 5 mg/kg bevacizumab) while maintaining effective drug levels in the tumor nodules, potentially reducing systemic toxicity. Conclusions: These findings suggest that administering oxaliplatin-based HIPEC during bevacizumab-induced vascular normalization could significantly improve drug penetration and enhance treatment efficacy. Full article

The development of new energy vehicles and road dust removal technologies presents opportunities for constructing urban ventilation systems based on road patterns. However, the impact of road system layouts on pedestrian-level wind environments remains insufficiently understood. This study utilizes the general-purpose CFD software Phoenics to analyze the effects of road orientation, width, density, and intersection configurations on block ventilation. The standard k-ε model and three-dimensional steady-state RANS equations are employed to calculate pedestrian-level mean air age as an indicator of ventilation efficiency. Grid convergence analysis and validation against previous wind tunnel measurements were conducted. Results show that road layouts influence overall ventilation efficiency by affecting airflow volume, direction, and velocity. Optimal ventilation occurs when road orientation aligns with the prevailing wind at 0° or exceeds 70°. Recommended widths for trunk, secondary, and local roads are 46 m, 30 m, and 18 m, respectively. Lower densities of local road systems enhance ventilation, while higher densities of trunk and secondary roads are beneficial. Intersection configurations impact airflow distribution, with windward segments aiding lateral ventilation of side roads. Finally, ventilation design strategies for road systems are proposed, offering potential for leveraging urban road networks to construct efficient ventilation systems. Full article

This article focuses on the analysis of a direct air-cooled rotor winding of a wound field synchronous machine, the innovation of which lies in the increase in the internal cooling surface, the cooling of the winding compared to the conventional inter-pole cooling, and the development of a CHT evaluation model accordingly. Conjugate heat transfer (CHT) analysis is used to explore the cooling efficacy of a parallel-cooled hollow-conductor winding of a salient-pole rotor and to identify a cooling performance map. The use of high current densities of 15–20 Arms/mm² in directly cooled windings requires high cooling intensity, which in the case of air cooling results not only in flow velocities above 15 m/s to ensure permissible operating temperatures, but also the need for coolant distribution and heat transfer studies. The experiments and calculations are based on a non-rotating machine and a wind tunnel using the same rotor coil(s). CHT-based thermal calculations provide not only reliable results compared to experimental work and lumped parameter thermal circuits with adjusted aggregate parameters, but also insight related to pressure and cooling flow distribution, thermal loads, and cooling integration issues that are necessary for the development of high power density and reliable electrical machines. The results of the air-cooling integration show that the desired high current density is achievable at the expense of high cooling intensity, where the air velocity ranges from 15 to 30 m/s and 30 to 55 m/s, distinguishing the air velocity of the hollow conductor and bypass channel, compared to the same coil in an electric machine and a wind tunnel at the similar thermal load and limit. Since the hot spot location depends on cooling integration and cooling intensity, modeling and estimating the cooling flow is essential in the development of wound-field synchronous machines. Full article

Swash plate axial piston pumps play an important role in hydraulic systems due to their superior performance and compact design. As the controlled object of the valve-controlled hydraulic cylinder, the swash plate is affected by the complex fluid dynamics effect and the mechanical structure, which is prone to vibration, during the working process, thereby adversely affecting the dynamic performance of the system. In this paper, an electronically controlled ball screw type variable displacement mechanism with stiffness compensation is proposed. By introducing piezoelectric ceramic materials into the nut assembly, dynamic stiffness compensation of the system is achieved, which effectively changes the vibration characteristics of the swash plate and thus significantly improves the working stability of the system. Based on this, the stiffness model of a double nut ball screw is established to obtain the relationship between piezoelectric ceramics and the double nut. An asymmetric Bouc–Wen piezoelectric actuator model with nonlinear hysteresis characteristics is also established, and a particle swarm algorithm with improved inertia weights is utilized to identify the parameters of the asymmetric Bouc–Wen model. Finally, a piezoelectric actuator model based on the feedforward inverse model and a PID composite control algorithm is applied to the variable displacement mechanism system for stiffness compensation. Full article

The core inlet flow distribution in the APR1000 reactor is critical for ensuring the reactors safety and efficient operation by maintaining uniform coolant flow across fuel assemblies. Previous studies, though insightful, faced challenges in fully replicating reactor-scale flow conditions due to technical and economic constraints associated with scaled-down experimental models and the limited numerical validation methodologies. This study addresses these limitations by developing and validating a robust computational fluid dynamics (CFD) methodology to accurately analyze the core inlet flow distribution. A 1/5 scaled-down experimental model adhering to similarity laws was employed for validation. CFD analyses using ANSYS Fluent and CFX, combined with turbulence model evaluations and grid sensitivity studies, demonstrated that the SST and RNG k-ε turbulence models provided the most accurate predictions, with a high correlation to previous experimental data. Full-scale simulations revealed uniform coolant distribution at the core inlet, with peripheral assemblies exhibiting higher flow rates, consistent with previous experimental observations. Quantitative metrics such as the coefficient of variation (COV), relative error (RD), and root mean square error (RMSE) confirmed the superior performance of the SST model in CFX, achieving a COV of 7.993% (experimental COV: 5.694%) and an RD of 0.047. This methodology not only validates the CFD approach but also highlights its applicability to reactor design optimization and safety assessment. The findings of this study provide critical guidelines for analyzing complex thermal-fluid systems in nuclear reactor designs. Full article

Modeling of thermal energy storage (TES) tanks with computational fluid dynamics (CFD) tools exhibits limitations that hinder the time, scalability, and standardization of the procedure. In this study, an innovative technique is proposed to overcome the challenges in CFD modeling of TES tanks. This study assessed the feasibility of employing neural networks for TES tank modeling, evaluating the similarities in terms of structure and signal-to-noise ratio by comparing images generated by neural networks with those produced through CFD simulations. The results regarding the structural similarity index indicate that around 94% of the images obtained have a similarity index above 0.9. For the signal-to-noise ratio, the results indicate a mean value of 25 dB, which can be considered acceptable, although indicating room for improvement. Additional results show that our neural network model obtains the best performance when working with initial states close to the stable phase of the TES tank. The results obtained in this study are promising, laying the groundwork for a future pathway that could potentially replace the current methods used for TES tank modeling. Full article

Pneumatic conveying technology is an efficient, energy-saving and environmentally friendly means of solid feed conveying. In the process of pneumatic conveying, wind speed has a decisive influence on conveying characteristics. Here, computational fluid dynamics coupled with a discrete element method simulation and experiment were combined, and the conveying wind speed was used as the experimental variable to study the conveying characteristics of the conveying material in the tube, such as particle distribution state, solid phase mass concentration, coupling force on solid feed, average speed and pressure drop of solid feed in the pipe. The results show that when the conveying wind speed increases from 18 m/s to 20.6 m/s, the solid feed changes from sedimentary flow to suspended flow, the particle accumulation gradually decreases and the conveying efficiency is significantly improved. The particle slug greatly reduces the collision and friction between the internal particles and the pipe and reduces the crushing rate to a certain extent. When the conveying wind speed is about 23.2 m/s, there are almost no trapped particles in the pipeline, which can achieve rapid feed delivery, and conveying efficiency is greatly improved. Therefore, this paper provides a good theoretical basis for improving conveying efficiency and reducing crushing rate in the process of pneumatic conveying. Full article

Biodiesel production has gained attention as a sustainable alternative to fossil fuels, but challenges related to catalyst recovery and energy consumption remain. In this study, a novel lithium-impregnated aluminosilicate catalyst (LiSA) was developed using a 3D-printed mold, providing precise control over its structure to optimize performance. The structured catalyst featured a cylindrical shape with multiple circular channels, enhancing fluid dynamics and reactant interaction in a fixed-bed reactor. Catalyst characterization by SEM, TGA, XRD, and ICP-MS confirmed high thermal stability and uniform pore distribution. Jatropha curcas oil was used as feedstock, with diethyl ether (DEE) acting as a cosolvent to improve methanol solubility and enable transesterification at room temperature. The process achieved a high fatty acid methyl ester (FAME) yield, averaging 97.1% over 508 min of continuous operation, demonstrating the catalyst’s stability and sustained activity. By reducing mass transfer limitations and energy demands, this approach highlights the potential of 3D-printed catalysts to advance sustainable biodiesel production, offering a scalable and efficient pathway for green energy technologies. Full article

In the design of fluid systems, rapid iteration and simulation verification are essential, and reduced-order modeling techniques can significantly improve computational efficiency and accuracy. However, traditional Physics-Informed Neural Networks (PINNs) often face challenges such as vanishing or exploding gradients when learning flow field characteristics, limiting their ability to capture complex fluid dynamics. This study presents an enhanced reduced-order model (ROM): Physics-Informed Neural Networks based on Residual Networks (Res-PINNs). By integrating a Residual Network (ResNet) module into the PINN architecture, the proposed model improves training stability while preserving physical constraints. Additionally, the model’s ability to capture and learn flow field states is further enhanced by the design of a symmetric parallel neural network structure. To evaluate the effectiveness of the Res-PINNs model, two classic fluid dynamics problems—flow around a cylinder and Vortex-Induced Vibration (VIV)—were selected for comparative testing. The results demonstrate that the Res-PINNs model not only reconstructs flow field states with higher accuracy but also effectively addresses limitations of traditional PINN methods, such as vanishing gradients, exploding gradients, and insufficient learning capacity. Compared to existing approaches, the proposed Res-PINNs provide a more stable and efficient solution for deep learning-based reduced-order modeling in fluid system design. Full article

This study focused on the novel ventilation solution used in the control room of an electric submersible pump on a jack-up offshore platform, with the core objective of exploring the advantages of tunnel ventilation over the traditional ceiling-mounted ventilation system. At the beginning of the research, a three-dimensional physical model of the room’s air conditioning and ventilation system was constructed using Rhino 7 software. Subsequently, the computational fluid dynamics software Airpak 3.0 was employed to conduct detailed thermodynamic calculations on the model. Based on this, the study meticulously compared the performance of the two ventilation systems from multiple perspectives: one aspect examined the airflow and temperature distribution through temperature contour maps, velocity vector maps, and airflow streamlines; another focused on the comfort level of personnel, as reflected in the key indicators of the predicted mean vote and predicted percentage dissatisfied. The results demonstrated that tunnel ventilation is highly effective in reducing the indoor temperature and significantly improving personnel comfort. Further optimization analysis revealed that, under specific inlet conditions, namely when the inlet velocity reaches 1.16 m/s and the inlet temperature is 17 °C, the most ideal ventilation effect can be achieved, thereby fully and effectively meeting human thermal comfort requirements. Overall, the findings of this study not only provide a novel solution for the environmental control system design of offshore platforms but also lay a solid scientific foundation for continued exploration in related fields, offering a reliable reference for future research. Full article

Microalgae-based CO₂ capture has potential as an industrial-scale solution to climate change challenges while also amassing usable microalgae biomass. Computational fluid dynamics (CFD) can optimize CO₂ extraction in microalgae growing systems, especially when paired with phytohormone-regulated growth. This paper examines the use of CFD to predict fluid flow, nutrient distribution, light intensity, and mass transfer in microalgae-based systems, which are crucial for improving photosynthetic efficiency and fixing CO₂. The focus is on how phytohormones, such as auxins and cytokinin, influence microalgal growth and their subsequent involvement in increasing carbon sequestration. Furthermore, this review discusses CFD applications in reactor design, where fluid dynamics and biological kinetics interact to increase biomass yield. The focus on scaling up and transitioning from laboratory to industrial application with the possible integration of computational fluid dynamics with experiment data to enhance simulation precision is addressed. The assessment demonstrates CFD’s potential as an important tool for sustainable CO₂ fixation. Full article

In electric vehicles (EVs), the batteries are arranged in the battery pack (BP), which has a small layout space and difficulty in dissipating heat. Therefore, in EVs, the battery thermal management systems (BTMSs) are critical to managing heat to ensure safety and performance, particularly under higher operating temperatures and longer discharge conditions. To solve this problem, in this article, the thermal analysis models of a 3-battery-cell BP were created, including scenarios (1) natural air cooling without a BTMS; (2) natural air cooling with water cooling hybrid BTMS; and (3) forced air cooling plus water cooling composite BTMS. The thermal performances of the pack-level BPs were simulated and analyzed based on computational fluid dynamics (CFD). A variety of boundary conditions and working parameters, such as ambient temperature, inlet coolant flow rate and initial temperature, discharge rate, air flow rate, and initial temperature, were considered. The results show that without a BTMS (Scenario 1), the maximum temperature in the BP rises rapidly and continuously to reach 63.8 °C, much higher than the upper bound of the recommended operating temperature range (ROTR between +20 °C to +35 °C) under the extreme discharge rate of 3 C and even if the discharge rate is 2 C. With a hybrid BTMS (Scenario 2), the maximum temperature in BP rises to about 38.7 °C, slightly above the upper bound of the ROTR. Lowering the coolant (water) initial temperature can effectively lower the temperature up to 5.7 °C in BP, but the water flow rate cannot since the turbulence model. While with a composite BTMS (Scenario 3), the temperature can be further lowered up to 1.5 °C under the extreme discharge rate of 3C, just reaching the upper bound of the ROTR. In addition, lowering the initial coolant temperature or air temperature can effectively decrease the temperatures up to 5.1 and 1.0 °C, respectively, in BP, but the coolant flow rate (due to the turbulence model) and the air flow rate cannot. Finally, the thermal performances of the different battery cells in the BP with different cooling systems and at the different positions of the BP were compared and analyzed. The present work may contribute to the design of BTMSs in the EV industry. Full article

Seasonal velocity variations can significantly impact the total energy delivered to microgrids produced by river hydrokinetic turbines. These turbines typically use a diffuser to increase the velocity at the rotor section, adding weight and raising deployment costs. There is a need for practical solutions to improve the capacity factor of such turbines. Our solution involves using multiple turbine rotors that can be interchanged to match seasonal velocity changes, eliminating shrouds to simplify design and reduce costs. This solution requires turbines that are designed to have an easily interchanged rotor, which requires us to limit the rotor to a two-blade design to also lower costs. This approach adjusts the turbine power curve with different two-blade rotor sizes, enhancing the yearly capacity factor. BladeGen ANSYS Workbench is used to design three two-blade rotors for free stream velocities of 1.6, 2.2, and 2.8 m/s. For each turbine rotor, 3D simulation is applied to reduce aerodynamic losses and target a coefficient of performance of about 45%. Mechanical stress analyses assess the displacement and stress of the used composite materials. Numerical results show good agreement with experimental data, with rotor efficiencies ranging from 43% to 45% at a tip speed ratio of 4 and power output between 5.4 and 5.6 kW. Results show that rotor interchangeability significantly enhances the turbine capacity factor, increasing it from 52% to 92% by adapting to river seasonal velocity changes. Full article

We extend the 3D Lattice Boltzmann method with a deformable boundary (LBM-DB) for the computations of the full-volume colonic flow of the Newtonian fluid driven by the peristaltic segmented circular contractions which obey the three-step “intestinal law”: (i) deflation, (ii) inflation, and (iii) elastic relaxation. The key point is that the LBM-DB accurately prescribes a curved deforming surface on the regular computational grid through precise and compact Dirichlet velocity schemes, without the need to recover for an adaptive boundary mesh or surface remesh, and without constraint of fluid volume conservation. The population “refill” of “fresh” fluid nodes, including sharp corners, is reformulated with the improved reconstruction algorithms by combining bulk and advanced boundary LBM steps with a local sub-iterative collision update. The efficient parallel LBM-DB simulations in silico then extend the physical experiments performed in vitro on the Dynamic Colon Model (DCM, 2020) to highly occlusive contractile waves. The motility scenarios are modeled both in a cylindrical tube and in a new geometry of “parabolic” transverse shape, which mimics the dynamics of realistic triangular lumen aperture. We examine the role of cross-sectional shape, motility pattern, occlusion scenario, peristaltic wave speed, elasticity effect, kinematic viscosity, inlet/outlet conditions and numerical compressibility on the temporal localization of pressure and velocity oscillations, and especially the ratio of retrograde vs antegrade velocity amplitudes, in relation to the major contractile events. The developed numerical approach could contribute to a better understanding of the intestinal physiology and pathology due to a possibility of its straightforward extension to the non-Newtonian chyme rheology and anatomical geometry. Full article