Computational Fluid Dynamics Model Research Articles

Study on simulated airflow dynamics of children with obstructive sleep apnea treated by different surgical methods

Objective:To analyze the effects of adenoidectomy, tonsillectomy and tonsillectomy combined with adenoidectomy on obstructive sleep apnea children by computational fluid dynamics numerical simulation. Methods:A case of typical tonsil with adenoid hypertrophy was selected. Mimics 21.0 software was used to establish the original preoperative model, adenoidectomy, tonsillectomy and virtual surgical models of tonsillectomy combined adenoidectomy, and the computational fluid dynamics model of the upper airway was established by ANSYS 2019 R1 software, and then the pressure and velocity of the internal flow field of the CFD model were numerically simulated. Seven planes perpendicular to the flow trace were selected as the observation planes, including the cross section of the sinusostoma complex, the anterior end of the adenoid body, the narrowest cross section of the nasopharyngeal cavity, the pharyngostoma tube, the narrowest cross section of the oropharyngeal cavity, the lower pole of the tonsil and the glottis section. The comparison indexes included pressure, flow velocity and flow distribution. Results:Compared with the original model before operation, after the adenoids were removed only, the pressure drop between the section of the ostiomeatal complex and the section of the eustachian tube decreased, the high velocity peak at the anterior end of the adenoids disappeared, and the flow trace through the middle nasal canal increased. When only bilateral tonsils were removed, the pressure drop between the eustachian tube and the glottis slowed down and the flow velocity between the eustachian tube and the glottis slowed down. Combined tonsillar-adenoidectomy resulted in the most uniform pressure distribution, the most gentle pressure change and flow rate in the upper airway, and the most ignificant increase in airflow trace through the middle nasal canal among the three operations. Conclusion:Adenoidectomy, tonsillectomy and combined tonsillar adenoidectomy can make the airflow velocity and pressure of upper respiratory tract uniform to different degrees, but there are obvious differences in the specific anatomical location and degree. The application of CFD can intuitively predict the improvement of upper airway flow field in OSA children by different surgical methods, which helps clinicians to make surgical decision.

Numerical investigation on the effect of ignition timing on a low-temperature hydrogen-fueled Wankel rotary engine with passive pre-chamber ignition

Adopting the low-temperature hydrogen evaporated from the liquid hydrogen is capable of improving volumetric efficiency for the Wankel rotary engine (WRE). Considering the difficulty in ignition and slow flame propagation of low-temperature hydrogen-air mixtures, the passive pre-chamber is used to improve ignition and combustion. A three-dimensional computational fluid dynamics model for a turbulent jet ignition (TJI) WRE fueled by low-temperature hydrogen was established. The effects of low temperature and TJI on the in-cylinder flow field, combustion, emissions and leakage in the TJI-WRE fueled by low-temperature hydrogen were studied under different ignition timings. The results indicated that low-temperature tends to suppress the flame propagation, whereas TJI can accelerate the flame speed and promote flame propagation to the unburned zone in the combustion chamber. Combining low-temperature hydrogen with the passive pre-chamber can achieve high engine thermal efficiency and power while significantly reducing leakage. With the ignition timing set at 18 °CA before the top dead center, the indicated thermal efficiency reached 39.49% and the indicated mean effective pressure peaked at 0.77 MPa. Compared to the original engine, fresh mixture leakage through spark plug cavities and adjacent chambers was reduced by 72.13% and 78.79%, respectively.

A computational fluid dynamics-based girth welding model for large-diameter pipeline to reveal vertical weld formation mechanism

Welding quality significantly impacts the safety of large-diameter, long-distance pipelines. The molten pool flow, influenced by gravity, results in variations in the girth weld seam at different circumferential orientations. A three-dimensional transient computational fluid dynamics model was developed to study the multi-layer, multi-pass welding process of X80M pipeline, incorporating arc heat, droplet heat, gravity, and fluid flow in the molten pool. The model also simulates dual-torch automatic welding to examine heat transfer and flow characteristics. Notably, it reveals the morphological evolution of the girth weld seam from the 2 to 3 o'clock positions during continuous welding, an area lacking prior research. The results, validated by experiments, show good agreement between the simulation and thermal cycle curves. The weld pool solidifies from the sides toward the center, creating a concave shape due to downward metal flow, with dual-torch welding intensifying this effect. The second torch increases the concavity of filler layers, with depths rising by 21.81% and 32.20%. These findings offer new insights into pipeline girth welding.

Exploration of the Out‐of‐Phase Phenomenon in Shake Flasks by CFD Calculations of Volumetric Power Input, kLa Value and Shear Rate at Elevated Viscosity

ABSTRACTCulture broth with secreted macromolecules and culture broth of filamentous fungi showing disperse growth exhibit elevated viscosity, usually with shear‐thinning flow behavior. High viscosity, however, poses a serious challenge in the production and research of these compounds and organisms. It commonly causes insufficient mixing and oxygen transfer in large‐ and small‐scale bioreactors. Computational Fluid dynamics (CFD) has been proven to be a valuable tool for the computation of important bioprocess parameters. The published literature for small‐scale shaken bioreactors, especially shake flasks, however, almost exclusively focuses on water‐like viscosity. In this paper, a previously published CFD model for 250 mL shake flasks was used to simulate experiments at high viscosities of up to 100 mPa·s. Compared to experimental data, the CFD model accurately predicted the liquid distribution and computed the volumetric power input with a deviation of less than 7% and the kLa value within a factor of two, compared to the kLa correlation from Henzler and Schedel. Furthermore, a novel approach to compute the shear rate was tested. Lastly, new insights into the out‐of‐phase phenomenon were gained. The presented data confirms the usefulness of the already established critical phase numbers of 0.91 and 1.26, while underlying the fundamentally smooth transition from in‐phase to out‐of‐phase operating conditions.

Phenol Concentration in Liquid Smoke Production from Rubberwood by Experiment and Simulation with CFD Modeling

Liquid smoke is produced through condensation resulting from the pyrolysis process of rubberwood, without the presence of oxygen. One of the dominant contents of liquid smoke products is phenol. Therefore, this study aimed to examine the molar concentration of simulated liquid smoke and the comparison between the experimental and simulated molar concentrations. The simulation used Ansys Fluent 19.2, a Computational Fluid Dynamics (CFD) program using the finite volume method in its solution. The several stages in completing Ansys simulation include pre-processing, meshing, processing, and post-processing. The geometry depicted in this study was a 2-dimensional pyrolysis reactor. Assumptions made for the simulation comprised using lignin as raw material, along with specified flowrate, and pyrolysis time. The results showed that based on the reaction mechanism, lignin in the pyrolysis process produced a phenol yield of 4.52%. In the final stage, quantitative data simulation results were obtained in the form of molar concentrations produced from liquid smoke products. The molar concentrations in the simulation during pyrolysis for 1, 2, 3, 4, and 5 hours were 0.00183512, 0.0017854, 0.00170856, 0.0017628, and 0.00166788 kmol/m3, respectively. The experimental molar concentration results also showed the same pattern as the simulation data. At 4 hours of pyrolysis, the molar concentration of phenol increased, resulting in liquid smoke with the best quality. A comparison of liquid smoke molar concentration for the simulation and experiment indicated a minimal difference of 0.005%.

Power Loss and Electrothermal Characterization of Hybrid Power Integrated Modules for Industrial Servo Motor Drives

This study aims to facilitate the assessment of the electromagnetic-electrical-thermal coupled response of a developed 30 kHz/12 kW silicon carbide (SiC)/silicon (Si) hybrid power-integrated module (hPIM) during load operation. To achieve this goal, an efficient electromagnetic-circuit-thermal coupling (ECTC) analysis methodology is introduced. This ECTC methodology incorporates a fully integrated electromagnetic-circuit coupling (EMCC) analysis model for parasitic extraction in order to addressing their effects on power losses, and a simplified electrothermal coupling (SETC) analysis model for temperature evaluation in order to consider the coupling influence of the instantaneous junction temperature on instantaneous power losses. The SETC model couples a simple lookup table that maps the power loss (P) in terms of the temperature (T) constructed using the developed EMCC model, and an equivalent Foster thermal network model established through three-dimensional (3D) computational fluid dynamics (CFD) thermal flow analysis. This PT lookup table, replacing the tedious and time-consuming EMCC simulation, is responsible for fast estimation of temperature-dependent power losses. The proposed analysis models, namely the CFD, EMCC, and SETC analysis models, are validated through thermal experiments and detailed modeling. Finally, the influence of various operation conditions on the power losses of the hPIM during the power conversion operation is explored through parametric analysis.

Real-Time Environmental Design Parameters and their Impact on the Performance of Passive Basin Solar Still: A Dynamic CFD Modeling Approach

A computational fluid dynamics (CFD) approach was used in this work to investigate various design and environmental factors and their impact on the performance of passive basin solar stills (PBSS). This requires using the ANSYS software to build a sophisticated geometrical solar still model with the associated solar cells. The impact of solar cell configuration on energy optimization was determined by analyzing the developed system in both series and parallel configurations. Accuracy of simulation results was ensured in the model by introducing a meshing technique that consisted of>2 million components. The results (for static pressure analysis) indicated the absence of any high-pressure-induced strains after evaluating the performance metrics (static pressure, velocity, and energy distribution) for impact on the system using > 200 iterations; this suggests that the system design is balanced. Hence, the performance of solar stills can be improved by using new materials and design configurations as shown in this work. This study has improved knowledge of solar water desalination and other forms of renewable energy sources for related applications.

On the Numerical Investigation of Two-Phase Evaporative Spray Cooling Technology for Data Centre Applications

Two-phase evaporative spray cooling technology can significantly reduce power consumption in data centre cooling applications. However, the literature lacks an established methodology for assessing the overall performance of such evaporation systems in terms of the water-energy nexus. The current study develops a Lagrangian–Eulerian computational fluid dynamics (CFD) modelling approach to examine the functionality of these two-phase evaporative spray cooling systems. To replicate a modular system, a hollow spray cone nozzle with Rosin–Rammler droplet size distribution is simulated in a turbulent convective natural-air environment. The model was validated against the available experimental data from the literature. Parametric studies on geometric, flow, and climatic conditions, namely, domain length, droplet size, water mass flow rate, temperature, and humidity, were performed. The findings indicate that at elevated temperatures and low humidity, evaporation results in a bulk temperature reduction of up to 12 °C. A specific focus on the climatic conditions of Dublin, Ireland, was used as an example to optimize the evaporative system. A new formulation for the coefficient of performance (COP) is established to assess the performance of the system. Results showed that doubling the injector water mass flow rate improved the evaporated mass flow rate by 188% but reduced the evaporation percentage by 28%, thus reducing the COP. Doubling the domain length improved the temperature drop by 175% and increased the relative humidity by 160%, thus improving the COP. The COP of the evaporation system showed a systematic improvement with a reduction in the droplet size and the mass flow rate for a fixed domain length. The evaporated system COP improves by two orders of magnitude (~90 to 9500) with the reduction in spray Sauter mean diameter (SMD) from 292 μm to 8–15 μm. Under this reduction, close to 100% evaporation rate was achieved in comparison to only a 1% evaporation rate for the largest SMD. It was concluded that the utilization of a fine droplet spray nozzle provides an effective solution for the reduction in water consumption (97% in our case) for data centres, whilst concomitantly augmenting the proportion of evaporation.

Integrated DNN and CFD model for real-time prediction of furnace waterwall slagging of coal-fired boiler

Slagging of furnace waterwall adversely affects the thermal performance and increases the operation and maintenance costs of coal-fired boilers. A real-time slagging prediction model is of great significance for the plant operators to monitor the furnace slagging conditions and make appropriate operation of soot blowers to maintain the cleanliness of waterwall. Three-dimensional (3D) computational fluid dynamics (CFD) can predict detailed furnace slagging distributions, but its high computational cost has been the major impediment hindering its application in large-scale combustion systems that require real-time information. To resolve this problem, a CFD-based deep neural network (DNN) model framework was developed in this study to realize the real-time prediction of furnace wall slagging distribution. A 3D CFD model was first developed and employed to generate the slagging database under typical boiler operating parameters. Then this database was utilized to train the DNN model to capture the mapping relationship between boiler operating parameters and wall slagging distributions. The core idea of this CFD-based DNN model is to generalize the wall slagging distributions under different boiler operating conditions based on this mapping relationship learned by the DNN model. This model was applied to a 350 MW coal-fired boiler. The prediction results by the CFD model demonstrated that the boiler operating parameters, such as boiler load and coal burner swirling blade angle, have strong effects on furnace wall slagging distributions, while the DNN model could precisely capture their relationship and make predictions with deviation from the CFD results below 5 %. More importantly, the DNN model could give the prediction results within seconds that is three to four orders of magnitude faster than the CFD model. Thus, it can respond to the rapidly changing boiler operating conditions and realize the real-time prediction of furnace wall slagging distributions.

Comparative study of turbulence models in CFD for transonic flow over the ONERA M6 wing

Transonic flight presents significant challenges due to complex phenomena such as shock waves and turbulent boundary layer interactions, often leading to flow separation and instabilities. This study aims to evaluate the performance of various turbulence models in predicting these phenomena using Computational Fluid Dynamics (CFD) with ANSYS-Fluent 2020R1. The ONERA M6 wing model is analyzed under specific flow conditions (angle of attack, α = 3.06°, Mach number, M∞ = 0.8395, and Reynolds number, Re = 11.72 × 10^6) to assess five turbulence models: Spalart–Allmaras, k-ε Standard, k-ε Realizable, k-ω Standard, and k-ω SST. Results from the simulations closely matched experimental data, with all models demonstrating a margin of error within 5% compared to NASA’s CFD benchmarks. Notably, the Spalart–Allmaras and k-ω SST models showed superior accuracy in predicting shock formation and pressure distribution, highlighting their potential for enhanced predictive capabilities in aerodynamic analysis. This study demonstrates the effectiveness of ANSYS-Fluent in aerodynamic performance evaluation and suggests pathways for advancing aircraft design efficiency and safety through improved turbulence modeling.

Evaluation of the effect of hemodynamic factors on retinal microcirculation by using 3D confocal image-based computational fluid dynamics

PurposeTo investigate local hemodynamic changes resulting from elevated intraocular pressure (IOP) in different vasculature networks using a computational fluid dynamics model based on 3D reconstructed confocal microscopic images.MethodsThree-dimensional rat retinal vasculature was reconstructed from confocal microscopy images using a 3D U-Net-based labeling technique, followed by manual correction. We conducted a computational fluid dynamics (CFD) analysis on different retinal vasculature networks derived from a single rat. Various venule and arteriole pressures were applied to mimic the effects of elevated intraocular pressure (IOP), a major glaucoma risk factor. An increase in IOP typically correlates with a decrease in venous pressure. We also varied the percentage of capillary dropout, simulating the loss of blood vessels within the capillary network, by reducing the volume of the normal capillary network by 10%, 30%, and 50%. Based on the output of the CFD analysis, we calculated velocity, wall shear stress (WSS), and pressure gradient for different vasculature densities.ResultsArteriolar pressure, venular pressure, and capillary dropout appear to be important factors influencing wall shear stress in the rat capillary network. Our study revealed that the pressure gradient between arterioles and venules strongly affects the local wall shear stress distribution across the 3D retinal vasculature. Specifically, under a pressure gradient of 3,250 Pa, the wall shear stress was found to vary between 0 and 20 Pa, with the highest shear stress observed in the region of the superficial layer. Additionally, capillary dropout led to a 25% increase or decrease in wall shear stress in affected areas.ConclusionThe hemodynamic differences under various arteriole and venule pressures, along with different capillary dropout conditions, could help explain the development of various optic disorders, such as glaucoma, diabetic retinopathy, and retinal vein occlusion.

Simulation of Fluid Flow through Orifice Meter

The modeling of fluid flow using an orifice meter is an engineering endeavor aimed at thoroughly investigating and optimizing fluid flow measurement in various industrial applications. Orifice meters are highly regarded for their accurate measurement of fluid flow rates as they pass through a specifically designed orifice plate, utilizing the principles of fluid dynamics. The primary objective of this project is to develop a computational fluid dynamics (CFD) model capable of simulating the intricate fluid flow through an orifice meter. The simulation encompasses detailed geometric features of the orifice meter, including the precise dimensions of the orifice plate, pipe diameter, and any relevant taper angles. Additionally, the model takes into account various fluid parameters, boundary conditions, and factors such as velocity and pressure at different points within the system. The comprehensive study visualizes and quantifies key fluid properties, such as velocity profiles, pressure differentials, and flow velocities, across the entire length of the orifice meter using CFD analysis. This in-depth analysis provides crucial insights into the dynamic performance of the orifice meter. The obtained information holds significant potential to revolutionize flow rate measurement accuracy, efficiency, and cost-effectiveness in diverse industries, including water management, chemical processing, and oil and gas. The project's methodology for simulating fluid flow through orifice meters can bring about substantial improvements in the understanding and optimization of fluid flow in industrial processes.

Modeling Airflow and Temperature in a Sealed Cold Storage System for Medicinal Plant Cultivation Using Computational Fluid Dynamics (CFD)

Effective air circulation is crucial for plant growth, requiring adequate airflow and environmental stability. This study utilized Computational Fluid Dynamics (CFD) to analyze airflow patterns in a controlled testing chamber, focusing on how miniature fan placement affects airflow direction and temperature distribution. Ten case studies were conducted, with the CFD model validated against experimental data collected from six monitoring locations on the plant growth table. Model validation was performed using statistical analyses including coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The validation results showed strong agreement between simulated and experimental data, with R2 values of 0.92 for temperature and 0.89 for airflow velocity. Statistical analysis showed significant differences in both airflow and temperature models at the 0.05 level, with the CFD model validation yielding an RMSE of 2.02 and an average absolute error of 1.17. Among the tested configurations, case M1 achieved the highest air velocity (0.317 m/s) and lowest temperature (27.03 °C), compared to M2 (0.255 m/s, 27.17 °C) and M3 (0.164 m/s, 27.18 °C). The temperature variations between cases significantly impacted cold storage efficiency, with case M1’s superior airflow distribution providing more uniform cooling. These findings offer practical guidelines for optimizing ventilation system design in medicinal plant cultivation facilities, particularly in maintaining ideal storage conditions through strategic fan placement and airflow management.

Modelling of coronary artery stenosis and study of hemodynamic under the influence of magnetic fields

Investigating magnetic blood flow characteristics through arteries and micron-size channels for clinical therapies in biomedicine is becoming increasingly important with the rise of point-of-care diagnostics devices. A computational fluid dynamics (CFD) investigation is conducted to explore blood flow within a coronary artery affected by an elliptical stenosis near the artery wall under the influence of a magnetic field. The novelty of our study is the integration of Navier-Stokes and Maxwell's equations to calculate body forces on fluid flow, coupled with the application of magnetic fields both longitudinally and vertically, and the use of the Carreau-Yasuda model to analyse non-Newtonian blood rheology. Blood flow is modelled by solving the incompressible continuity and momentum equations, considering laminar and non-Newtonian properties, with the finite element-based solver COMSOL Multiphysics. The CFD model is validated using previously published analytical and computational data. This study investigates the effects of magnetic fields on blood flow through stenotic arteries with 25 %, 35 %, and 50 % stenosis, examining how the magnetic field and its orientation impact variations in velocity profiles, pressure drop, and wall shear stress (WSS). Our results show that magnetic fields can effectively manipulate blood flow, causing acceleration or deceleration depending on field direction. Significant changes in hemodynamics are observed, particularly at 50 % arterial stenosis, highlighting the profound impact of stenosis on flow characteristics. Compared to healthy arteries, the velocity change in stenosed arteries increased by 16.5 %, 29.4 %, and 62.1 % for 25 %, 35 %, and 50 % stenosis, respectively. The findings advance experimental models of blood flow in magnetic fields, highlighting the critical importance of regulating blood velocity and pressure. These insights are particularly valuable for developing drug delivery systems and magnetic-driven blood pumps.

A sizing model for a tube in tube sensible thermal energy storage heat exchanger with solid storage material

Sensible thermal energy storage (STES) systems are generally the most affordable and least complex type of thermal energy storage systems available. The main question when modeling STES systems is the outlet state of the heat transfer fluid for a given inlet condition. Traditional heat exchanger design methods such as the logarithmic mean temperature difference method do not apply to TES systems since these systems do not operate in steady state. Other design methods are only applicable to specific cases such as packed bed systems with a thermocline. The present paper proposes a novel framework for STES system design with solid, stationary storage material. The framework is validated based on the case of a tube in tube STES system. The novel design model characterizes the local conductive heat transfer in the Laplace domain. This local behavior is integrated over the surface of the heat exchanger using three methods: a height split, a height lumped and a fully lumped approach. Each method corresponds to a different assumption regarding the temperature gradient in the storage material and will therefore be applicable to different cases. By numerically inverting the Laplace transform, a prediction is obtained of the outlet temperature of the HTF in the time domain. The solution is compared to the result of a computational fluid dynamics (CFD) reference model for five selected cases, with the CFD requiring calculation times in the order of days on a dedicated server while the novel model requires seconds on a laptop. This difference in calculation time is the result of the need of the CFD model to discretize the domain in space and apply a time stepping algorithm. The transfer function approach requires neither discretization nor time stepping but it does require a numerical inverse Laplace transform. The transfer function approach has a good fit with the CFD predictions. Furthermore, the quality of the fit and the behavior of the system is predicted based on the Biot number, the thermocline width ratio and the cross conduction number where the latter two numbers are derived in the present paper. The novel approach can provide a method to obtain sizing models for STES systems with a solid storage material.

Computational Fluid Dynamics Modeling and Analysis of Lime Slurry Drying in a Laboratory Spray Dry Scrubber

Computational Fluid Dynamics Modeling and Analysis of Lime Slurry Drying in a Laboratory Spray Dry Scrubber

Development of a Machine Learning Natural Ventilation Rate Model by Studying the Wind Field Inside and Around Multiple-Row Chinese Solar Greenhouses

This paper experimented with a methodology of machine learning modelling using virtual samples generated by fast CFD (Computational Fluid Dynamics) simulations in order to predict the greenhouse natural ventilation. However, the output natural ventilation rates using fast two-dimensional (2D) CFD models are not always consistent with the three-dimensional (3D) one for all the scenarios. The first contribution of this paper is a proposed comparative modelling methodology between two-dimensional and three-dimensional CFD studies, regarding its validity, especially when buildings are in rows. The results show that the error of the ventilation rate prediction could exceed 50%, if 2D models are not properly used. Subsequently, in those scenarios where the 2D and the 3D models had equal accuracy, nearly one thousand samples were generated using fast 2D CFD simulations to train a natural ventilation rate regression tree model. This model is efficient to deal with the combined effect of wind pressure and thermal gradients under various vent configurations, with only four necessary inputs. In addition, by analyzing the wind speed distribution contour of the outdoor wind field around the greenhouse rows, the optimal wind speed-measuring locations were determined to eliminate interference for predicting the natural ventilation rate.

CFD simulation of liquid nitrogen flow inside a cryogenic chamber used for micromachining of soft polymer

Cryogenic-assisted micromachining is seen as a possible solution to fabricate microchannel directly on soft polymer, by increasing the stiffness of the workpiece surface by reducing cryogenic chamber temperature. However, because of large temperature difference at various position of the cooling area inside the chamber, under cryogenic cooling condition, determination of workpiece temperature at machining time is very difficult. Unfortunately, very limited research work has investigated the complicated physical phenomena of cryogenic cooling responsible for temperature distribution occurring inside the chamber during machining process. These phenomena may affect the cryogenic flow characteristics in over or under-cooling of soft polymer as workpiece, thus the performance of the cryogenic machining. In this work, computational fluid dynamic (CFD) model is developed and applied to investigate the liquid nitrogen (LN2) flow inside the cryogenic chamber under direct cooling (DC) and novel perforated wall cooling (PWC) techniques. The major objective is to evaluate the influence of several parameters (temperature and pressure) on the LN2 flow inside the chamber and role of the innovative PWC technique in temperature distribution with comparison to DC approach. Results of this study offer two important conclusions for reliable cryogenic micromilling of soft polymer. First, uniform temperature distribution inside the chamber is possible by novel PWC approach and second, peripheral temperature of the chamber shows less fluctuation with surface temperature of the workpiece.

Evaluation of flow and heat transfer behavior in parallel flow copper electro-refining cell with different inlet arrangements

Parallel flow copper electro-refining cell technology has been developed for over a decade, and the flow field in these cells is significantly influenced by the arrangement of the electrolyte inlets. Four computational fluid dynamics models were developed to compare the flow and heat transfer characteristics of the electrolyte under varying electrolyte inlet arrangements. These models include bi-directional parallel flow (BPF), staggered parallel flow (SPF), top inlet unidirectional parallel flow (UPF-T), and bottom inlet unidirectional parallel flow (UPF-B). Flow and heat transfer simulations were conducted for each model. The simulation results indicate that the BPF and SPF electro-refining cells exhibit varying degrees of kinetic energy loss, which leads to lower volume-weighted average velocities and impacts the rapid circulation of the electrolyte. The UPF-B is the most effective in terms of both flow uniformity and flow velocity, with the UPF-T following closely behind. The temperature in the inter-pole area is elevated when the SPF and UPF-T are arranged, which is more conducive to the diffusion of copper ions. The copper cathode production efficiency and deposition uniformity are enhanced by the UPF-B arrangement, which enables the liquid to be supplied to the inter-pole area more rapidly and uniformly.

Numerical Investigation of Combustion and Emission Characteristics of the Single-Cylinder Diesel Engine Fueled with Diesel-Ammonia Mixture

This study proposes a dual-fuel approach combining diesel and ammonia in a single-cylinder compression ignition engine to reduce harmful emissions from internal combustion. Diesel is directly injected into the combustion chamber, while ammonia is introduced through the intake manifold with intake air. In this study, injection timing and the percentage of ammonia energy fraction was varied. A computational fluid dynamics (CFD) model simulates the combustion and emission processes to assess the impact of varying diesel injection timings and ammonia energy contributions. Findings indicate that as ammonia content increases, the engine experiences reductions in peak in-cylinder pressure, temperature, heat release rate, as well as overall efficiency and power output. Emission results suggest that greater ammonia usage leads to a reduction in soot, carbon monoxide, carbon dioxide, and unburned hydrocarbons, though a slight increase in nitrogen oxides emissions is observed. This analysis supports ammonia’s potential as a low-emission alternative fuel in future compression ignition engines.